Skip to content

Regression

Model Dataset MAE RMSE R2 Memory in Mb Time in s
Adaptive Model Rules ChickWeights 24.0925 37.1369 0.719675 0.0469542 5.03028
Adaptive Model Rules TrumpApproval 1.40204 2.43644 -1.02749 0.114429 5.76779
Adaptive Random Forest ChickWeights 25.9648 40.6034 0.6649 1.18613 32.8286
Adaptive Random Forest TrumpApproval 0.801133 2.11603 -0.529292 1.28362 54.6942
Bagging ChickWeights 23.0595 36.5862 0.727928 0.643575 19.8658
Bagging TrumpApproval 0.904415 2.23483 -0.705833 1.33501 42.6904
Exponentially Weighted Average ChickWeights 120.54 139.462 -2.95334 0.183387 12.3806
Exponentially Weighted Average TrumpApproval 40.7536 40.7895 -567.257 0.316642 30.0432
Hoeffding Adaptive Tree ChickWeights 23.2557 37.579 0.712962 0.0946112 5.75782
Hoeffding Adaptive Tree TrumpApproval 0.910675 2.2343 -0.705019 0.138225 6.69917
Hoeffding Tree ChickWeights 23.0842 36.6638 0.726773 0.0440512 4.02236
Hoeffding Tree TrumpApproval 0.949745 2.24815 -0.726224 0.148639 9.13796
Linear Regression ChickWeights 23.8353 37.0287 0.721307 0.00421047 2.10647
Linear Regression TrumpApproval 1.3486 4.12828 -4.82084 0.00497341 3.6327
Linear Regression with l1 regularization ChickWeights 23.868 37.0773 0.720575 0.00444126 1.13401
Linear Regression with l1 regularization TrumpApproval 1.21585 4.06821 -4.65269 0.0052042 2.06156
Linear Regression with l2 regularization ChickWeights 25.5204 38.6553 0.696284 0.00423336 1.11618
Linear Regression with l2 regularization TrumpApproval 1.99918 4.40997 -5.64232 0.0049963 1.98704
Passive-Aggressive Regressor, mode 1 ChickWeights 24.2339 37.5576 0.713289 0.00345898 1.33977
Passive-Aggressive Regressor, mode 1 TrumpApproval 4.90639 6.6656 -14.1749 0.00443554 2.18425
Passive-Aggressive Regressor, mode 2 ChickWeights 99.5681 141.4 -3.06396 0.00345898 1.99155
Passive-Aggressive Regressor, mode 2 TrumpApproval 31.1288 34.4257 -403.774 0.00443554 2.19594
River MLP ChickWeights 49.5783 77.9026 -0.233541 0.0123129 18.4913
River MLP TrumpApproval 1.59139 5.147 -8.04808 0.0133505 30.7873
Stochastic Gradient Tree ChickWeights 68.1198 79.5649 -0.286746 1.12059 9.48214
Stochastic Gradient Tree TrumpApproval 9.43874 17.9468 -109.008 3.08244 24.6638
Streaming Random Patches ChickWeights 23.5162 38.2072 0.703285 0.558536 50.7829
Streaming Random Patches TrumpApproval 0.640561 1.97134 -0.32731 1.05934 101.873
[baseline] Mean predictor ChickWeights 49.4914 70.2457 -0.00297194 0.000490189 0.529127
[baseline] Mean predictor TrumpApproval 1.56814 2.20374 -0.658701 0.000490189 0.8379
k-Nearest Neighbors ChickWeights 22.9043 34.7945 0.753924 0.0461216 4.35991
k-Nearest Neighbors TrumpApproval 0.493975 1.50807 0.223232 0.0660038 9.48546

Try reloading the page if something is buggy

{ "$schema": "https://vega.github.io/schema/vega-lite/v5.json", "data": { "values": [ { "step": 11, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 32.364564569910335, "RMSE": 32.97872020361878, "R2": -1398.9905780691188, "Memory in Mb": 0.0041303634643554, "Time in s": 0.003051 }, { "step": 22, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 22.977933628105813, "RMSE": 25.38362603225939, "R2": -681.3960169454474, "Memory in Mb": 0.0041303634643554, "Time in s": 0.0083 }, { "step": 33, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 16.216942910977988, "RMSE": 20.82463881551788, "R2": -300.18738429635704, "Memory in Mb": 0.0041303634643554, "Time in s": 0.014943 }, { "step": 44, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 12.450847696587651, "RMSE": 18.04722398474583, "R2": -255.42929659358052, "Memory in Mb": 0.0041303634643554, "Time in s": 0.023007 }, { "step": 55, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 11.8883407017882, "RMSE": 18.699705575978975, "R2": -67.26141846932143, "Memory in Mb": 0.0041303634643554, "Time in s": 0.032524 }, { "step": 66, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 11.481406471145082, "RMSE": 17.562600262725994, "R2": -24.95549321582236, "Memory in Mb": 0.0041303634643554, "Time in s": 0.043462 }, { "step": 77, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 10.781108661026623, "RMSE": 16.493572764286025, "R2": -14.34295652053857, "Memory in Mb": 0.0041303634643554, "Time in s": 0.055844 }, { "step": 88, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 9.717703273355898, "RMSE": 15.46585610846664, "R2": -11.231382330967593, "Memory in Mb": 0.0041303634643554, "Time in s": 0.069657 }, { "step": 99, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 8.826979124235404, "RMSE": 14.601347274688614, "R2": -8.118374730562003, "Memory in Mb": 0.0041303634643554, "Time in s": 0.084902 }, { "step": 110, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 8.34720326953035, "RMSE": 13.931298318002057, "R2": -4.796525071049026, "Memory in Mb": 0.0041303634643554, "Time in s": 0.101965 }, { "step": 121, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 8.037877082888846, "RMSE": 13.41080638289134, "R2": -3.136902586442697, "Memory in Mb": 0.0041303634643554, "Time in s": 0.120474 }, { "step": 132, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 7.656433924417384, "RMSE": 12.898278689410905, "R2": -2.1275837609073576, "Memory in Mb": 0.0041303634643554, "Time in s": 0.140407 }, { "step": 143, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 7.307942088554156, "RMSE": 12.437137940834392, "R2": -1.3553409371460328, "Memory in Mb": 0.0041303634643554, "Time in s": 0.161783 }, { "step": 154, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 7.037714222368383, "RMSE": 12.042115748312936, "R2": -0.8765797740197239, "Memory in Mb": 0.0041303634643554, "Time in s": 0.184594 }, { "step": 165, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 7.129031762481882, "RMSE": 11.913307711374014, "R2": -0.4764258010150459, "Memory in Mb": 0.0041303634643554, "Time in s": 0.208855 }, { "step": 176, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 7.184514897799321, "RMSE": 11.77636646389892, "R2": -0.1632359842489146, "Memory in Mb": 0.0041303634643554, "Time in s": 0.23453 }, { "step": 187, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 7.115123062484693, "RMSE": 11.572523949602724, "R2": 0.0802677819230903, "Memory in Mb": 0.0041303634643554, "Time in s": 0.261536 }, { "step": 198, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 7.006474290899419, "RMSE": 11.366304822809298, "R2": 0.2942397460202306, "Memory in Mb": 0.0041303634643554, "Time in s": 0.289991 }, { "step": 209, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 7.129008217053805, "RMSE": 11.440940870898142, "R2": 0.4105268603250641, "Memory in Mb": 0.0041303634643554, "Time in s": 0.319876 }, { "step": 220, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 7.62421928608864, "RMSE": 12.045617517752785, "R2": 0.4279229250366536, "Memory in Mb": 0.0041303634643554, "Time in s": 0.351191 }, { "step": 231, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 7.729844807682863, "RMSE": 12.068921171072352, "R2": 0.5087708730950672, "Memory in Mb": 0.0041303634643554, "Time in s": 0.383941 }, { "step": 242, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 7.873703200353374, "RMSE": 12.23342730557754, "R2": 0.5938836560989084, "Memory in Mb": 0.0041303634643554, "Time in s": 0.4181169999999999 }, { "step": 253, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 7.894340397324045, "RMSE": 12.218207932001455, "R2": 0.6481596201604607, "Memory in Mb": 0.0041303634643554, "Time in s": 0.4537249999999999 }, { "step": 264, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 8.479294890454037, "RMSE": 13.126132095776898, "R2": 0.6289858847198173, "Memory in Mb": 0.0042104721069335, "Time in s": 0.4907699999999999 }, { "step": 275, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 8.914096443559163, "RMSE": 13.971715828104037, "R2": 0.6301108693673194, "Memory in Mb": 0.0042104721069335, "Time in s": 0.529253 }, { "step": 286, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 9.123963222012373, "RMSE": 14.305597328390173, "R2": 0.6641373552910966, "Memory in Mb": 0.0042104721069335, "Time in s": 0.569186 }, { "step": 297, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 9.083791720841957, "RMSE": 14.24670706195338, "R2": 0.7111028643570333, "Memory in Mb": 0.0042104721069335, "Time in s": 0.610599 }, { "step": 308, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 9.589205789771716, "RMSE": 14.956254664628933, "R2": 0.716435491318643, "Memory in Mb": 0.0042104721069335, "Time in s": 0.653398 }, { "step": 319, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 10.6480954226875, "RMSE": 17.335456678654833, "R2": 0.654294294845865, "Memory in Mb": 0.0042104721069335, "Time in s": 0.697581 }, { "step": 330, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 11.061417554605155, "RMSE": 17.89416376383148, "R2": 0.6847745473646168, "Memory in Mb": 0.0042104721069335, "Time in s": 0.743241 }, { "step": 341, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 11.240970714084437, "RMSE": 17.96809449059472, "R2": 0.7153933828209167, "Memory in Mb": 0.0042104721069335, "Time in s": 0.7902760000000001 }, { "step": 352, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 11.393007763406809, "RMSE": 18.07679096199219, "R2": 0.7381404893604309, "Memory in Mb": 0.0042104721069335, "Time in s": 0.8386990000000001 }, { "step": 363, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 12.251680566634816, "RMSE": 19.3891577397662, "R2": 0.7074601934283691, "Memory in Mb": 0.0042104721069335, "Time in s": 0.8885620000000001 }, { "step": 374, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 12.75183556333798, "RMSE": 20.473547618215623, "R2": 0.7001526953506461, "Memory in Mb": 0.0042104721069335, "Time in s": 0.93984 }, { "step": 385, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 13.120977867369843, "RMSE": 21.06680160073653, "R2": 0.7191139726408686, "Memory in Mb": 0.0042104721069335, "Time in s": 0.992561 }, { "step": 396, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 13.243904830041805, "RMSE": 21.04850718241465, "R2": 0.7385587649833809, "Memory in Mb": 0.0042104721069335, "Time in s": 1.046701 }, { "step": 407, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 14.114140715648691, "RMSE": 22.50284796635845, "R2": 0.7222415724766076, "Memory in Mb": 0.0042104721069335, "Time in s": 1.102244 }, { "step": 418, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 14.877176135328032, "RMSE": 23.91912678123439, "R2": 0.7054123344015044, "Memory in Mb": 0.0042104721069335, "Time in s": 1.159239 }, { "step": 429, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 15.420211528669606, "RMSE": 24.826921056607983, "R2": 0.71797392321154, "Memory in Mb": 0.0042104721069335, "Time in s": 1.2176479999999998 }, { "step": 440, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 15.588380621816588, "RMSE": 24.89946727120753, "R2": 0.7364018543257719, "Memory in Mb": 0.0042104721069335, "Time in s": 1.277456 }, { "step": 451, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 16.102138383202178, "RMSE": 25.5012042182244, "R2": 0.73526123694725, "Memory in Mb": 0.0042104721069335, "Time in s": 1.338723 }, { "step": 462, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 17.19666374070754, "RMSE": 27.602141070792264, "R2": 0.7086782414730581, "Memory in Mb": 0.0042104721069335, "Time in s": 1.4014049999999998 }, { "step": 473, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 17.97145397683086, "RMSE": 28.90516312323801, "R2": 0.7179019616037816, "Memory in Mb": 0.0042104721069335, "Time in s": 1.4654839999999998 }, { "step": 484, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 18.29792978215437, "RMSE": 29.184271659667463, "R2": 0.728186505594778, "Memory in Mb": 0.0042104721069335, "Time in s": 1.531041 }, { "step": 495, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 18.74962346435519, "RMSE": 29.70957841185893, "R2": 0.7350194821983969, "Memory in Mb": 0.0042104721069335, "Time in s": 1.597992 }, { "step": 506, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 19.63242676502778, "RMSE": 31.145843529930996, "R2": 0.717244444772776, "Memory in Mb": 0.0042104721069335, "Time in s": 1.666343 }, { "step": 517, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 20.352340621675207, "RMSE": 32.13418072986834, "R2": 0.7159654376794024, "Memory in Mb": 0.0042104721069335, "Time in s": 1.736162 }, { "step": 528, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 21.13777985928475, "RMSE": 33.324214910779105, "R2": 0.7253645356808669, "Memory in Mb": 0.0042104721069335, "Time in s": 1.807369 }, { "step": 539, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 21.30552841968683, "RMSE": 33.32197733500869, "R2": 0.7367405849979859, "Memory in Mb": 0.0042104721069335, "Time in s": 1.880014 }, { "step": 550, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 22.28842093535661, "RMSE": 34.93191609140748, "R2": 0.7196038878445231, "Memory in Mb": 0.0042104721069335, "Time in s": 1.954091 }, { "step": 561, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 22.98790385213596, "RMSE": 35.84862508987654, "R2": 0.7176082524890277, "Memory in Mb": 0.0042104721069335, "Time in s": 2.029559 }, { "step": 572, "track": "Regression", "model": "Linear Regression", "dataset": "ChickWeights", "MAE": 23.835304128485923, "RMSE": 37.028707868367256, "R2": 0.7213067136137974, "Memory in Mb": 0.0042104721069335, "Time in s": 2.106474 }, { "step": 20, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 23.20376765378399, "RMSE": 26.086393589237737, "R2": -1595.1823041445402, "Memory in Mb": 0.0048131942749023, "Time in s": 0.006002 }, { "step": 40, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 14.037845165976735, "RMSE": 19.010285970857197, "R2": -144.292318589198, "Memory in Mb": 0.0048131942749023, "Time in s": 0.015135 }, { "step": 60, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 11.507970876430278, "RMSE": 16.25440462414082, "R2": -142.20309184289852, "Memory in Mb": 0.0048131942749023, "Time in s": 0.026737 }, { "step": 80, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 9.557907896578074, "RMSE": 14.248619966820993, "R2": -109.38231735939875, "Memory in Mb": 0.0048131942749023, "Time in s": 0.04106 }, { "step": 100, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 8.00119890237694, "RMSE": 12.784639272000032, "R2": -54.757167221204185, "Memory in Mb": 0.0048131942749023, "Time in s": 0.058228 }, { "step": 120, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 6.9642139928158, "RMSE": 11.706689332840265, "R2": -38.660847151370525, "Memory in Mb": 0.0048131942749023, "Time in s": 0.078171 }, { "step": 140, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 6.158017211594616, "RMSE": 10.855926078196225, "R2": -34.244125473921144, "Memory in Mb": 0.0048131942749023, "Time in s": 0.100823 }, { "step": 160, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 5.477712824897756, "RMSE": 10.159717829752896, "R2": -26.22221848793916, "Memory in Mb": 0.0048131942749023, "Time in s": 0.126265 }, { "step": 180, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 5.024407839120485, "RMSE": 9.597258286357787, "R2": -20.33422740878964, "Memory in Mb": 0.0048131942749023, "Time in s": 0.154466 }, { "step": 200, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 4.585662202332267, "RMSE": 9.108145701438088, "R2": -18.272229834363905, "Memory in Mb": 0.0048131942749023, "Time in s": 0.185533 }, { "step": 220, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 4.26060909213789, "RMSE": 8.692057179629266, "R2": -17.933082537971817, "Memory in Mb": 0.0048131942749023, "Time in s": 0.219335 }, { "step": 240, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 3.9717866152166015, "RMSE": 8.326248244302885, "R2": -16.503720237291063, "Memory in Mb": 0.0048131942749023, "Time in s": 0.255864 }, { "step": 260, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 3.713770572650404, "RMSE": 8.00217875002923, "R2": -15.385557669694744, "Memory in Mb": 0.0049734115600585, "Time in s": 0.2951479999999999 }, { "step": 280, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 3.519033617242816, "RMSE": 7.718418241237259, "R2": -14.960370233444367, "Memory in Mb": 0.0049734115600585, "Time in s": 0.3371889999999999 }, { "step": 300, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 3.3459125962612686, "RMSE": 7.4642342223287805, "R2": -13.679347912302555, "Memory in Mb": 0.0049734115600585, "Time in s": 0.382005 }, { "step": 320, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 3.2142611116185447, "RMSE": 7.238080925352425, "R2": -13.486769876410833, "Memory in Mb": 0.0049734115600585, "Time in s": 0.429554 }, { "step": 340, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 3.0579195410777067, "RMSE": 7.023783188903098, "R2": -13.41588572736102, "Memory in Mb": 0.0049734115600585, "Time in s": 0.479826 }, { "step": 360, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 2.945682332324278, "RMSE": 6.834004497968132, "R2": -12.75946181118139, "Memory in Mb": 0.0049734115600585, "Time in s": 0.532818 }, { "step": 380, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 2.834623050495076, "RMSE": 6.655478314361804, "R2": -12.501407484394289, "Memory in Mb": 0.0049734115600585, "Time in s": 0.588545 }, { "step": 400, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 2.750580257859316, "RMSE": 6.492898516140861, "R2": -12.2130072039923, "Memory in Mb": 0.0049734115600585, "Time in s": 0.647075 }, { "step": 420, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 2.6430441633874877, "RMSE": 6.337629923196658, "R2": -12.005235448499764, "Memory in Mb": 0.0049734115600585, "Time in s": 0.708317 }, { "step": 440, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 2.55209658354648, "RMSE": 6.194505226365406, "R2": -11.19965041203295, "Memory in Mb": 0.0049734115600585, "Time in s": 0.7723099999999999 }, { "step": 460, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 2.456089002686458, "RMSE": 6.059000096335146, "R2": -10.068304379054997, "Memory in Mb": 0.0049734115600585, "Time in s": 0.8388639999999999 }, { "step": 480, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 2.366054305985814, "RMSE": 5.93188196569365, "R2": -9.364683952709628, "Memory in Mb": 0.0049734115600585, "Time in s": 0.907942 }, { "step": 500, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 2.2878529832492878, "RMSE": 5.812913918334153, "R2": -8.7442989221461, "Memory in Mb": 0.0049734115600585, "Time in s": 0.979676 }, { "step": 520, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 2.2263077878678064, "RMSE": 5.701877933590318, "R2": -8.391958889485423, "Memory in Mb": 0.0049734115600585, "Time in s": 1.054282 }, { "step": 540, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 2.159275760054389, "RMSE": 5.596308740310266, "R2": -8.01424271274666, "Memory in Mb": 0.0049734115600585, "Time in s": 1.13157 }, { "step": 560, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 2.121286703179314, "RMSE": 5.500929056902255, "R2": -7.917124287747498, "Memory in Mb": 0.0049734115600585, "Time in s": 1.211538 }, { "step": 580, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 2.058130800812745, "RMSE": 5.4056516105350205, "R2": -7.823875188349783, "Memory in Mb": 0.0049734115600585, "Time in s": 1.294212 }, { "step": 600, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 2.010772210317983, "RMSE": 5.316298216027806, "R2": -7.440165070210115, "Memory in Mb": 0.0049734115600585, "Time in s": 1.379521 }, { "step": 620, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.9712240547218984, "RMSE": 5.232121316388296, "R2": -7.05039272692726, "Memory in Mb": 0.0049734115600585, "Time in s": 1.467481 }, { "step": 640, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.918906116628168, "RMSE": 5.150155111235484, "R2": -6.654334565315682, "Memory in Mb": 0.0049734115600585, "Time in s": 1.558 }, { "step": 660, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.87787066207154, "RMSE": 5.072802363597129, "R2": -6.372735616761029, "Memory in Mb": 0.0049734115600585, "Time in s": 1.651027 }, { "step": 680, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.8268195769848845, "RMSE": 4.997758130035794, "R2": -6.2693000939147145, "Memory in Mb": 0.0049734115600585, "Time in s": 1.746732 }, { "step": 700, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.786028440025988, "RMSE": 4.9266674679383895, "R2": -6.249499636750513, "Memory in Mb": 0.0049734115600585, "Time in s": 1.84509 }, { "step": 720, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.7407901109286728, "RMSE": 4.857855812572241, "R2": -6.20325679847918, "Memory in Mb": 0.0049734115600585, "Time in s": 1.946268 }, { "step": 740, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.6980813320245582, "RMSE": 4.791872643159282, "R2": -6.00468916158508, "Memory in Mb": 0.0049734115600585, "Time in s": 2.050093 }, { "step": 760, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.6641755726043943, "RMSE": 4.729168490426344, "R2": -5.896482494172518, "Memory in Mb": 0.0049734115600585, "Time in s": 2.156434 }, { "step": 780, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.6304504193200038, "RMSE": 4.6685949390255965, "R2": -5.751055148180852, "Memory in Mb": 0.0049734115600585, "Time in s": 2.265329 }, { "step": 800, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.6024144632936517, "RMSE": 4.610765602340218, "R2": -5.644394777378336, "Memory in Mb": 0.0049734115600585, "Time in s": 2.376883 }, { "step": 820, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.5772046524793362, "RMSE": 4.555342563217192, "R2": -5.556843815680599, "Memory in Mb": 0.0049734115600585, "Time in s": 2.490967 }, { "step": 840, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.5504230286371177, "RMSE": 4.501494961913348, "R2": -5.462190804899245, "Memory in Mb": 0.0049734115600585, "Time in s": 2.607626 }, { "step": 860, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.5213504760602443, "RMSE": 4.449264316210896, "R2": -5.302224210455831, "Memory in Mb": 0.0049734115600585, "Time in s": 2.72689 }, { "step": 880, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.4920620594434295, "RMSE": 4.398585386750051, "R2": -5.128866413959423, "Memory in Mb": 0.0049734115600585, "Time in s": 2.848697 }, { "step": 900, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.4631535468073946, "RMSE": 4.3495699730724, "R2": -5.018290064232882, "Memory in Mb": 0.0049734115600585, "Time in s": 2.973079 }, { "step": 920, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.4376774845864433, "RMSE": 4.302379067062498, "R2": -4.985157602999735, "Memory in Mb": 0.0049734115600585, "Time in s": 3.100144 }, { "step": 940, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.415413283450155, "RMSE": 4.2569033587476754, "R2": -4.909007968017405, "Memory in Mb": 0.0049734115600585, "Time in s": 3.229628 }, { "step": 960, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.3929189597034646, "RMSE": 4.212790914002432, "R2": -4.847686152244137, "Memory in Mb": 0.0049734115600585, "Time in s": 3.361574 }, { "step": 980, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.3689716642677323, "RMSE": 4.1697584324400925, "R2": -4.840094251784054, "Memory in Mb": 0.0049734115600585, "Time in s": 3.49595 }, { "step": 1000, "track": "Regression", "model": "Linear Regression", "dataset": "TrumpApproval", "MAE": 1.348598310616665, "RMSE": 4.128277744647548, "R2": -4.8208398605179, "Memory in Mb": 0.0049734115600585, "Time in s": 3.6327 }, { "step": 11, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 32.42675747760146, "RMSE": 33.032143455333795, "R2": -1403.530028209614, "Memory in Mb": 0.0043611526489257, "Time in s": 0.002172 }, { "step": 22, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 23.11671120534681, "RMSE": 25.467535638550565, "R2": -685.9150105173057, "Memory in Mb": 0.0043611526489257, "Time in s": 0.005938 }, { "step": 33, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 16.40645850052153, "RMSE": 20.90890407573329, "R2": -302.6297778360383, "Memory in Mb": 0.0043611526489257, "Time in s": 0.010657 }, { "step": 44, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 12.633013937743208, "RMSE": 18.123648450153382, "R2": -257.60569409037487, "Memory in Mb": 0.0043611526489257, "Time in s": 0.016312 }, { "step": 55, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 12.09340740686418, "RMSE": 18.75532087846616, "R2": -67.66805855020911, "Memory in Mb": 0.0043611526489257, "Time in s": 0.022822 }, { "step": 66, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 11.723217014070244, "RMSE": 17.64468538999345, "R2": -25.19868487320792, "Memory in Mb": 0.0043611526489257, "Time in s": 0.030046 }, { "step": 77, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 10.995180265837302, "RMSE": 16.56912334002292, "R2": -14.483838555564008, "Memory in Mb": 0.0043611526489257, "Time in s": 0.037972 }, { "step": 88, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 9.883907021821408, "RMSE": 15.530287677810511, "R2": -11.333507781967656, "Memory in Mb": 0.0043611526489257, "Time in s": 0.046598 }, { "step": 99, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 8.972176235897166, "RMSE": 14.66146594146288, "R2": -8.193616152032533, "Memory in Mb": 0.0043611526489257, "Time in s": 0.055927 }, { "step": 110, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 8.50780758363674, "RMSE": 13.99831063395296, "R2": -4.852424068253989, "Memory in Mb": 0.0043611526489257, "Time in s": 0.066187 }, { "step": 121, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 8.189643323772653, "RMSE": 13.479618530659062, "R2": -3.1794651999709123, "Memory in Mb": 0.0043611526489257, "Time in s": 0.077165 }, { "step": 132, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 7.801679323915957, "RMSE": 12.961634417305982, "R2": -2.158384304610562, "Memory in Mb": 0.0043611526489257, "Time in s": 0.088845 }, { "step": 143, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 7.451861020480359, "RMSE": 12.498785048420814, "R2": -1.3787482214976663, "Memory in Mb": 0.0043611526489257, "Time in s": 0.101232 }, { "step": 154, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 7.149646459280303, "RMSE": 12.093459492377487, "R2": -0.8926161646086501, "Memory in Mb": 0.0043611526489257, "Time in s": 0.114319 }, { "step": 165, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 7.229782522017506, "RMSE": 11.96532542528415, "R2": -0.4893471433346175, "Memory in Mb": 0.0043611526489257, "Time in s": 0.128105 }, { "step": 176, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 7.272512426798904, "RMSE": 11.818048782353436, "R2": -0.1714850789711801, "Memory in Mb": 0.0043611526489257, "Time in s": 0.1426069999999999 }, { "step": 187, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 7.196746625780547, "RMSE": 11.610365671998538, "R2": 0.0742429673312855, "Memory in Mb": 0.0043611526489257, "Time in s": 0.1578139999999999 }, { "step": 198, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 7.1064479168500405, "RMSE": 11.42347112116664, "R2": 0.2871227171728154, "Memory in Mb": 0.0043611526489257, "Time in s": 0.173728 }, { "step": 209, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 7.187961051781539, "RMSE": 11.470757896418933, "R2": 0.4074503232991815, "Memory in Mb": 0.0043611526489257, "Time in s": 0.1903399999999999 }, { "step": 220, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 7.669011107337858, "RMSE": 12.056664202246258, "R2": 0.426873173509426, "Memory in Mb": 0.0043611526489257, "Time in s": 0.2076519999999999 }, { "step": 231, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 7.786810512364482, "RMSE": 12.097059810994589, "R2": 0.5064776054701067, "Memory in Mb": 0.0043611526489257, "Time in s": 0.2256619999999999 }, { "step": 242, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 7.967587416991401, "RMSE": 12.312376354870244, "R2": 0.5886249568088757, "Memory in Mb": 0.0043611526489257, "Time in s": 0.2443719999999999 }, { "step": 253, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 7.942191618805254, "RMSE": 12.251768500136135, "R2": 0.6462241186586895, "Memory in Mb": 0.0043611526489257, "Time in s": 0.2637739999999999 }, { "step": 264, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 8.532657015260138, "RMSE": 13.159069559279288, "R2": 0.6271215737447722, "Memory in Mb": 0.0044412612915039, "Time in s": 0.2838889999999999 }, { "step": 275, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 8.974527826218258, "RMSE": 14.016709692996267, "R2": 0.6277246858047626, "Memory in Mb": 0.0044412612915039, "Time in s": 0.3047049999999999 }, { "step": 286, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 9.187875132430849, "RMSE": 14.367497338174372, "R2": 0.6612245262436964, "Memory in Mb": 0.0044412612915039, "Time in s": 0.3262349999999999 }, { "step": 297, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 9.146460078204475, "RMSE": 14.316362398212211, "R2": 0.7082709930315267, "Memory in Mb": 0.0044412612915039, "Time in s": 0.3484709999999999 }, { "step": 308, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 9.641370323857412, "RMSE": 15.001693346690402, "R2": 0.7147098761119641, "Memory in Mb": 0.0044412612915039, "Time in s": 0.3714179999999999 }, { "step": 319, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 10.700825117113602, "RMSE": 17.38383679543193, "R2": 0.6523619983610591, "Memory in Mb": 0.0044412612915039, "Time in s": 0.3950729999999999 }, { "step": 330, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 11.121905143066762, "RMSE": 17.96551370253039, "R2": 0.6822557197544588, "Memory in Mb": 0.0044412612915039, "Time in s": 0.4194319999999999 }, { "step": 341, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 11.300130820443067, "RMSE": 18.038310133249198, "R2": 0.7131646675929553, "Memory in Mb": 0.0044412612915039, "Time in s": 0.4444929999999999 }, { "step": 352, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 11.446939695127732, "RMSE": 18.13441953669637, "R2": 0.7364682185789984, "Memory in Mb": 0.0044412612915039, "Time in s": 0.4702589999999999 }, { "step": 363, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 12.306713664516929, "RMSE": 19.446501901626007, "R2": 0.7057272396553849, "Memory in Mb": 0.0044412612915039, "Time in s": 0.4967349999999999 }, { "step": 374, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 12.8047145381729, "RMSE": 20.530886427306594, "R2": 0.6984708214392588, "Memory in Mb": 0.0044412612915039, "Time in s": 0.523921 }, { "step": 385, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 13.174415073298738, "RMSE": 21.133761140382827, "R2": 0.7173255769005842, "Memory in Mb": 0.0044412612915039, "Time in s": 0.551805 }, { "step": 396, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 13.2883642577537, "RMSE": 21.10340115690396, "R2": 0.7371933225224319, "Memory in Mb": 0.0044412612915039, "Time in s": 0.580392 }, { "step": 407, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 14.156717848187574, "RMSE": 22.549679209142333, "R2": 0.7210842693854467, "Memory in Mb": 0.0044412612915039, "Time in s": 0.6096860000000001 }, { "step": 418, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 14.91944953335544, "RMSE": 23.967687063528587, "R2": 0.7042149845564116, "Memory in Mb": 0.0044412612915039, "Time in s": 0.6396860000000001 }, { "step": 429, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 15.467166242517186, "RMSE": 24.886955839016704, "R2": 0.7166083213097005, "Memory in Mb": 0.0044412612915039, "Time in s": 0.6704000000000001 }, { "step": 440, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 15.631989433801651, "RMSE": 24.954278611820005, "R2": 0.735240056765428, "Memory in Mb": 0.0044412612915039, "Time in s": 0.7018220000000001 }, { "step": 451, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 16.140858755557055, "RMSE": 25.549476814516595, "R2": 0.7342580119275103, "Memory in Mb": 0.0044412612915039, "Time in s": 0.7339490000000001 }, { "step": 462, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 17.234115417053438, "RMSE": 27.64913352119068, "R2": 0.7076854506057617, "Memory in Mb": 0.0044412612915039, "Time in s": 0.766781 }, { "step": 473, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 18.0152369206823, "RMSE": 28.967470484053976, "R2": 0.7166844816496443, "Memory in Mb": 0.0044412612915039, "Time in s": 0.800319 }, { "step": 484, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 18.33784663215877, "RMSE": 29.23326362096376, "R2": 0.727273146935064, "Memory in Mb": 0.0044412612915039, "Time in s": 0.834558 }, { "step": 495, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 18.785497932712666, "RMSE": 29.755293652524703, "R2": 0.7342033839127224, "Memory in Mb": 0.0044412612915039, "Time in s": 0.86951 }, { "step": 506, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 19.668627686193567, "RMSE": 31.19471320280161, "R2": 0.7163564282233008, "Memory in Mb": 0.0044412612915039, "Time in s": 0.90517 }, { "step": 517, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 20.38947136061499, "RMSE": 32.18441644636668, "R2": 0.7150766748346216, "Memory in Mb": 0.0044412612915039, "Time in s": 0.941543 }, { "step": 528, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 21.174247281712567, "RMSE": 33.375214332088184, "R2": 0.7245232875146275, "Memory in Mb": 0.0044412612915039, "Time in s": 0.978621 }, { "step": 539, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 21.335113723003413, "RMSE": 33.369412847265615, "R2": 0.7359905254430201, "Memory in Mb": 0.0044412612915039, "Time in s": 1.016405 }, { "step": 550, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 22.319908918673335, "RMSE": 34.98038586656285, "R2": 0.7188252208291055, "Memory in Mb": 0.0044412612915039, "Time in s": 1.054903 }, { "step": 561, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 23.02102944586984, "RMSE": 35.899425045778656, "R2": 0.7168073485461736, "Memory in Mb": 0.0044412612915039, "Time in s": 1.094104 }, { "step": 572, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "ChickWeights", "MAE": 23.86795045847124, "RMSE": 37.077313876148, "R2": 0.7205745757906983, "Memory in Mb": 0.0044412612915039, "Time in s": 1.134008 }, { "step": 20, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 23.431235633428948, "RMSE": 26.218144216470428, "R2": -1611.3462157506035, "Memory in Mb": 0.0050439834594726, "Time in s": 0.004147 }, { "step": 40, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 14.103513545807008, "RMSE": 19.087149489688155, "R2": -145.46960290724672, "Memory in Mb": 0.0050439834594726, "Time in s": 0.010783 }, { "step": 60, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 11.461367198760032, "RMSE": 16.23222714650599, "R2": -141.81258639462544, "Memory in Mb": 0.0050439834594726, "Time in s": 0.018889 }, { "step": 80, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 9.44127715126052, "RMSE": 14.201674320759096, "R2": -108.65615123709478, "Memory in Mb": 0.0050439834594726, "Time in s": 0.028452 }, { "step": 100, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 7.797022024035496, "RMSE": 12.721240349043525, "R2": -54.205539694816935, "Memory in Mb": 0.0050439834594726, "Time in s": 0.039551 }, { "step": 120, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 6.691147023027369, "RMSE": 11.629122321270428, "R2": -38.13701304656029, "Memory in Mb": 0.0050439834594726, "Time in s": 0.052122 }, { "step": 140, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 5.831783229321132, "RMSE": 10.770680162674168, "R2": -33.69279126993988, "Memory in Mb": 0.0050439834594726, "Time in s": 0.066155 }, { "step": 160, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 5.153144449790517, "RMSE": 10.076741978726949, "R2": -25.77937886024605, "Memory in Mb": 0.0050439834594726, "Time in s": 0.08166 }, { "step": 180, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 4.653806702754108, "RMSE": 9.504457154537077, "R2": -19.92363756907144, "Memory in Mb": 0.0050439834594726, "Time in s": 0.098629 }, { "step": 200, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 4.222103651464603, "RMSE": 9.017588926226493, "R2": -17.890910704295415, "Memory in Mb": 0.0050439834594726, "Time in s": 0.117152 }, { "step": 220, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 3.8867321432249606, "RMSE": 8.600346446062781, "R2": -17.535660715889627, "Memory in Mb": 0.0050439834594726, "Time in s": 0.137154 }, { "step": 240, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 3.599340946609919, "RMSE": 8.235553698215059, "R2": -16.124474758948196, "Memory in Mb": 0.0050439834594726, "Time in s": 0.15861 }, { "step": 260, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 3.3420538385748757, "RMSE": 7.912854669167724, "R2": -15.021792727856036, "Memory in Mb": 0.0052042007446289, "Time in s": 0.181525 }, { "step": 280, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 3.121876705697044, "RMSE": 7.625390851691296, "R2": -14.577959242562436, "Memory in Mb": 0.0052042007446289, "Time in s": 0.205897 }, { "step": 300, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 2.9443386382725367, "RMSE": 7.3683114276631025, "R2": -13.30448388815742, "Memory in Mb": 0.0052042007446289, "Time in s": 0.231796 }, { "step": 320, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 2.815755936756583, "RMSE": 7.138230019587049, "R2": -13.089830522149688, "Memory in Mb": 0.0052042007446289, "Time in s": 0.259173 }, { "step": 340, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 2.6933833627330244, "RMSE": 6.928597052658441, "R2": -13.027805837336182, "Memory in Mb": 0.0052042007446289, "Time in s": 0.288012 }, { "step": 360, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 2.6051143953909115, "RMSE": 6.739167122054826, "R2": -12.380223856378365, "Memory in Mb": 0.0052042007446289, "Time in s": 0.318313 }, { "step": 380, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 2.490520088621087, "RMSE": 6.560408055638074, "R2": -12.118440379947032, "Memory in Mb": 0.0052042007446289, "Time in s": 0.350072 }, { "step": 400, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 2.379600080775968, "RMSE": 6.3947378153227445, "R2": -11.816514349639151, "Memory in Mb": 0.0052042007446289, "Time in s": 0.383345 }, { "step": 420, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 2.2783211278818065, "RMSE": 6.240996339547436, "R2": -11.61166202267384, "Memory in Mb": 0.0052042007446289, "Time in s": 0.418092 }, { "step": 440, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 2.2145782025697205, "RMSE": 6.101000859547544, "R2": -10.83412932108482, "Memory in Mb": 0.0052042007446289, "Time in s": 0.454298 }, { "step": 460, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 2.1464112051078263, "RMSE": 5.968705291729145, "R2": -9.740869666058233, "Memory in Mb": 0.0052042007446289, "Time in s": 0.491959 }, { "step": 480, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 2.072454283271577, "RMSE": 5.843773480387036, "R2": -9.059069500744918, "Memory in Mb": 0.0052042007446289, "Time in s": 0.5310900000000001 }, { "step": 500, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.9987939253418097, "RMSE": 5.726023081885353, "R2": -8.45516263823347, "Memory in Mb": 0.0052042007446289, "Time in s": 0.5716870000000001 }, { "step": 520, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.9284894530733132, "RMSE": 5.614979238753044, "R2": -8.107866604370331, "Memory in Mb": 0.0052042007446289, "Time in s": 0.613828 }, { "step": 540, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.8708966196370944, "RMSE": 5.510640598064868, "R2": -7.740375491210358, "Memory in Mb": 0.0052042007446289, "Time in s": 0.657455 }, { "step": 560, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.824494929332068, "RMSE": 5.412971505312132, "R2": -7.634241934578528, "Memory in Mb": 0.0052042007446289, "Time in s": 0.702504 }, { "step": 580, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.781951127238344, "RMSE": 5.3203622791847724, "R2": -7.547628985954546, "Memory in Mb": 0.0052042007446289, "Time in s": 0.748994 }, { "step": 600, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.749732390051898, "RMSE": 5.233421242207161, "R2": -7.179064952823026, "Memory in Mb": 0.0052042007446289, "Time in s": 0.796981 }, { "step": 620, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.7052484400139905, "RMSE": 5.14921027958835, "R2": -6.797272491389374, "Memory in Mb": 0.0052042007446289, "Time in s": 0.846385 }, { "step": 640, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.6664817162996513, "RMSE": 5.068963198399273, "R2": -6.414896594696412, "Memory in Mb": 0.0052042007446289, "Time in s": 0.897251 }, { "step": 660, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.6214900718153242, "RMSE": 4.99171743637858, "R2": -6.138924064419633, "Memory in Mb": 0.0052042007446289, "Time in s": 0.949568 }, { "step": 680, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.5818233283584242, "RMSE": 4.918048415051679, "R2": -6.03927170869104, "Memory in Mb": 0.0052042007446289, "Time in s": 1.003319 }, { "step": 700, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.555259840641907, "RMSE": 4.848763195223404, "R2": -6.02204294951599, "Memory in Mb": 0.0052042007446289, "Time in s": 1.058593 }, { "step": 720, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.532054525069809, "RMSE": 4.783346185353484, "R2": -5.983984772166844, "Memory in Mb": 0.0052042007446289, "Time in s": 1.1153050000000002 }, { "step": 740, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.5146024654094865, "RMSE": 4.7215191517857305, "R2": -5.800515662606876, "Memory in Mb": 0.0052042007446289, "Time in s": 1.1734340000000003 }, { "step": 760, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.4818289913711118, "RMSE": 4.659306491272199, "R2": -5.694229888242945, "Memory in Mb": 0.0052042007446289, "Time in s": 1.2330550000000002 }, { "step": 780, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.452402157072035, "RMSE": 4.59956290700914, "R2": -5.552882667907455, "Memory in Mb": 0.0052042007446289, "Time in s": 1.294088 }, { "step": 800, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.4293016341621465, "RMSE": 4.542852809132106, "R2": -5.450103306475059, "Memory in Mb": 0.0052042007446289, "Time in s": 1.356613 }, { "step": 820, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.4031025761620075, "RMSE": 4.487566758646917, "R2": -5.363185739412862, "Memory in Mb": 0.0052042007446289, "Time in s": 1.420603 }, { "step": 840, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.381369306663701, "RMSE": 4.43470615373713, "R2": -5.271853959037296, "Memory in Mb": 0.0052042007446289, "Time in s": 1.48601 }, { "step": 860, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.3592027324075535, "RMSE": 4.3834303912536, "R2": -5.11710119981194, "Memory in Mb": 0.0052042007446289, "Time in s": 1.552867 }, { "step": 880, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.3365452172324814, "RMSE": 4.3337346544721145, "R2": -4.949476248649982, "Memory in Mb": 0.0052042007446289, "Time in s": 1.621167 }, { "step": 900, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.309932841675593, "RMSE": 4.285399956971287, "R2": -4.842022075269781, "Memory in Mb": 0.0052042007446289, "Time in s": 1.690888 }, { "step": 920, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.286195364366444, "RMSE": 4.238743982476022, "R2": -4.809417914789597, "Memory in Mb": 0.0052042007446289, "Time in s": 1.762146 }, { "step": 940, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.270754149650798, "RMSE": 4.194574036632911, "R2": -4.737236102715975, "Memory in Mb": 0.0052042007446289, "Time in s": 1.834847 }, { "step": 960, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.252007480522268, "RMSE": 4.151199175197265, "R2": -4.677947706919012, "Memory in Mb": 0.0052042007446289, "Time in s": 1.908959 }, { "step": 980, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.2327553756112288, "RMSE": 4.10900051997898, "R2": -4.671141158917876, "Memory in Mb": 0.0052042007446289, "Time in s": 1.984552 }, { "step": 1000, "track": "Regression", "model": "Linear Regression with l1 regularization", "dataset": "TrumpApproval", "MAE": 1.2158544056174447, "RMSE": 4.0682125513101886, "R2": -4.652689174637866, "Memory in Mb": 0.0052042007446289, "Time in s": 2.061558 }, { "step": 11, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 32.49979765090093, "RMSE": 33.085767570527814, "R2": -1408.093935143081, "Memory in Mb": 0.0041532516479492, "Time in s": 0.00221 }, { "step": 22, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 23.548763427243948, "RMSE": 25.711783397814365, "R2": -699.1539821884553, "Memory in Mb": 0.0041532516479492, "Time in s": 0.0060149999999999 }, { "step": 33, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 16.994606748791693, "RMSE": 21.16216382986949, "R2": -310.0297747454571, "Memory in Mb": 0.0041532516479492, "Time in s": 0.010773 }, { "step": 44, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 13.434663043069094, "RMSE": 18.386175360023177, "R2": -265.1519301746234, "Memory in Mb": 0.0041532516479492, "Time in s": 0.016452 }, { "step": 55, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 12.685726760044922, "RMSE": 18.64479618798502, "R2": -66.86112450289035, "Memory in Mb": 0.0041532516479492, "Time in s": 0.023006 }, { "step": 66, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 12.3059577367172, "RMSE": 17.58876192176611, "R2": -25.03287862681572, "Memory in Mb": 0.0041532516479492, "Time in s": 0.030252 }, { "step": 77, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 11.844694328458631, "RMSE": 16.6807536659431, "R2": -14.693178357367543, "Memory in Mb": 0.0041532516479492, "Time in s": 0.03818 }, { "step": 88, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 11.154725738202892, "RMSE": 15.783555067193374, "R2": -11.739056703820452, "Memory in Mb": 0.0041532516479492, "Time in s": 0.046793 }, { "step": 99, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 10.383929359740238, "RMSE": 14.970988963724652, "R2": -8.585892537614809, "Memory in Mb": 0.0041532516479492, "Time in s": 0.056087 }, { "step": 110, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 9.96579366260941, "RMSE": 14.36848414897767, "R2": -5.166041463970149, "Memory in Mb": 0.0041532516479492, "Time in s": 0.066275 }, { "step": 121, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 9.69456937849415, "RMSE": 13.920059192886765, "R2": -3.4570517192093604, "Memory in Mb": 0.0041532516479492, "Time in s": 0.077161 }, { "step": 132, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 9.550940690791585, "RMSE": 13.540299798742517, "R2": -2.4466881997122822, "Memory in Mb": 0.0041532516479492, "Time in s": 0.088733 }, { "step": 143, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 9.359343163302276, "RMSE": 13.17888693683795, "R2": -1.6446630191344274, "Memory in Mb": 0.0041532516479492, "Time in s": 0.100994 }, { "step": 154, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 9.050096583806178, "RMSE": 12.809003240652473, "R2": -1.1232058766616235, "Memory in Mb": 0.0041532516479492, "Time in s": 0.113939 }, { "step": 165, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 9.0176805612097, "RMSE": 12.690905771048246, "R2": -0.6754526017728211, "Memory in Mb": 0.0041532516479492, "Time in s": 0.127575 }, { "step": 176, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 9.128420828629457, "RMSE": 12.67565049026222, "R2": -0.3476766887041909, "Memory in Mb": 0.0041532516479492, "Time in s": 0.141896 }, { "step": 187, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 9.200055067293626, "RMSE": 12.61943948921252, "R2": -0.0936676208508318, "Memory in Mb": 0.0041532516479492, "Time in s": 0.156913 }, { "step": 198, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 9.131920516304556, "RMSE": 12.48608852319409, "R2": 0.14832986501041, "Memory in Mb": 0.0041532516479492, "Time in s": 0.172621 }, { "step": 209, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 9.262178084838377, "RMSE": 12.632807163510387, "R2": 0.2813122010719644, "Memory in Mb": 0.0041532516479492, "Time in s": 0.18901 }, { "step": 220, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 9.624585089266471, "RMSE": 13.14522964439942, "R2": 0.3187088278286061, "Memory in Mb": 0.0041532516479492, "Time in s": 0.206079 }, { "step": 231, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 9.871229105762628, "RMSE": 13.33182219595452, "R2": 0.4005868940419749, "Memory in Mb": 0.0041532516479492, "Time in s": 0.223824 }, { "step": 242, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 10.053594156641497, "RMSE": 13.615837484576032, "R2": 0.496913232046656, "Memory in Mb": 0.0041532516479492, "Time in s": 0.242255 }, { "step": 253, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 10.103586276318884, "RMSE": 13.654347763291469, "R2": 0.5605873283913356, "Memory in Mb": 0.0041532516479492, "Time in s": 0.261365 }, { "step": 264, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 10.539757430756955, "RMSE": 14.361033144769577, "R2": 0.5558923432468688, "Memory in Mb": 0.0042333602905273, "Time in s": 0.281177 }, { "step": 275, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 11.000663746720075, "RMSE": 15.253690514733572, "R2": 0.5591184315358017, "Memory in Mb": 0.0042333602905273, "Time in s": 0.301675 }, { "step": 286, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 11.301045102393736, "RMSE": 15.716738058687294, "R2": 0.5946085911267809, "Memory in Mb": 0.0042333602905273, "Time in s": 0.32286 }, { "step": 297, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 11.275670942063872, "RMSE": 15.722526759958118, "R2": 0.648148884657232, "Memory in Mb": 0.0042333602905273, "Time in s": 0.344736 }, { "step": 308, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 11.737413962135747, "RMSE": 16.425717512690383, "R2": 0.6579773485389515, "Memory in Mb": 0.0042333602905273, "Time in s": 0.367308 }, { "step": 319, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 12.62956768598283, "RMSE": 18.5239816734196, "R2": 0.6052658886851463, "Memory in Mb": 0.0042333602905273, "Time in s": 0.390571 }, { "step": 330, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 13.20835169207171, "RMSE": 19.400144953397177, "R2": 0.6294827674482892, "Memory in Mb": 0.0042333602905273, "Time in s": 0.41452 }, { "step": 341, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 13.34580485099439, "RMSE": 19.47322215763284, "R2": 0.6657152345574865, "Memory in Mb": 0.0042333602905273, "Time in s": 0.439156 }, { "step": 352, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 13.572829398695534, "RMSE": 19.644456145190084, "R2": 0.6907528542453616, "Memory in Mb": 0.0042333602905273, "Time in s": 0.464482 }, { "step": 363, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 14.286348966120116, "RMSE": 20.694687599962585, "R2": 0.666738740088638, "Memory in Mb": 0.0042333602905273, "Time in s": 0.490494 }, { "step": 374, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 14.777113556436731, "RMSE": 21.8206517710938, "R2": 0.6593962849465681, "Memory in Mb": 0.0042333602905273, "Time in s": 0.517211 }, { "step": 385, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 15.215863000720542, "RMSE": 22.583610768099227, "R2": 0.6772102871974224, "Memory in Mb": 0.0042333602905273, "Time in s": 0.544615 }, { "step": 396, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 15.33144965807796, "RMSE": 22.564695888148663, "R2": 0.6995373757169706, "Memory in Mb": 0.0042333602905273, "Time in s": 0.5727059999999999 }, { "step": 407, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 16.156138146741625, "RMSE": 23.924755047114477, "R2": 0.6860306363812331, "Memory in Mb": 0.0042333602905273, "Time in s": 0.601482 }, { "step": 418, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 16.826141311926307, "RMSE": 25.281544830782227, "R2": 0.6708975363085852, "Memory in Mb": 0.0042333602905273, "Time in s": 0.6309469999999999 }, { "step": 429, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 17.40263926327312, "RMSE": 26.38004441662919, "R2": 0.6815842184892376, "Memory in Mb": 0.0042333602905273, "Time in s": 0.6611069999999999 }, { "step": 440, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 17.533400796677356, "RMSE": 26.42712307382207, "R2": 0.7030645738539452, "Memory in Mb": 0.0042333602905273, "Time in s": 0.6919729999999998 }, { "step": 451, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 18.01931805998843, "RMSE": 26.98764790902567, "R2": 0.7034989551644695, "Memory in Mb": 0.0042333602905273, "Time in s": 0.7235269999999998 }, { "step": 462, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 19.02005973582853, "RMSE": 28.983219342716676, "R2": 0.6787962347144068, "Memory in Mb": 0.0042333602905273, "Time in s": 0.7557739999999998 }, { "step": 473, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 19.888963224686226, "RMSE": 30.578078926209333, "R2": 0.6843036130043219, "Memory in Mb": 0.0042333602905273, "Time in s": 0.7887069999999998 }, { "step": 484, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 20.14556805064173, "RMSE": 30.710181129007665, "R2": 0.6990197135707891, "Memory in Mb": 0.0042333602905273, "Time in s": 0.8223269999999998 }, { "step": 495, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 20.606054171923702, "RMSE": 31.270986299633183, "R2": 0.7064351021760091, "Memory in Mb": 0.0042333602905273, "Time in s": 0.8566339999999998 }, { "step": 506, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 21.410220326067677, "RMSE": 32.615082621422005, "R2": 0.6899384474766328, "Memory in Mb": 0.0042333602905273, "Time in s": 0.8916409999999998 }, { "step": 517, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 22.149063292155795, "RMSE": 33.66176418126127, "R2": 0.6883188968774838, "Memory in Mb": 0.0042333602905273, "Time in s": 0.9273449999999998 }, { "step": 528, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 22.923596011881333, "RMSE": 34.92960124509041, "R2": 0.6982661596564212, "Memory in Mb": 0.0042333602905273, "Time in s": 0.9637369999999996 }, { "step": 539, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 23.042465823580866, "RMSE": 34.93124976178739, "R2": 0.7106985365247873, "Memory in Mb": 0.0042333602905273, "Time in s": 1.0008159999999997 }, { "step": 550, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 23.974366627279803, "RMSE": 36.47485289150521, "R2": 0.6942867450600009, "Memory in Mb": 0.0042333602905273, "Time in s": 1.0385829999999998 }, { "step": 561, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 24.688352372874245, "RMSE": 37.45551228620605, "R2": 0.6917248794696187, "Memory in Mb": 0.0042333602905273, "Time in s": 1.077041 }, { "step": 572, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "ChickWeights", "MAE": 25.52040552278537, "RMSE": 38.65530944983144, "R2": 0.6962839796503111, "Memory in Mb": 0.0042333602905273, "Time in s": 1.116183 }, { "step": 20, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 23.51586240468561, "RMSE": 26.237375459551668, "R2": -1613.712423965852, "Memory in Mb": 0.004836082458496, "Time in s": 0.004083 }, { "step": 40, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 14.404588626352648, "RMSE": 19.15618772462805, "R2": -146.53108046561562, "Memory in Mb": 0.004836082458496, "Time in s": 0.01063 }, { "step": 60, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 12.231791081689297, "RMSE": 16.474815193156783, "R2": -146.113106004694, "Memory in Mb": 0.004836082458496, "Time in s": 0.018597 }, { "step": 80, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 9.897294138330498, "RMSE": 14.380930849374858, "R2": -111.44182781593445, "Memory in Mb": 0.004836082458496, "Time in s": 0.027966 }, { "step": 100, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 8.086918618304638, "RMSE": 12.871841233853624, "R2": -55.52038254270653, "Memory in Mb": 0.004836082458496, "Time in s": 0.038819 }, { "step": 120, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 7.090525087262731, "RMSE": 11.800543733353924, "R2": -39.29933105483862, "Memory in Mb": 0.004836082458496, "Time in s": 0.051073 }, { "step": 140, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 6.252895179240796, "RMSE": 10.939748534807466, "R2": -34.79049149741283, "Memory in Mb": 0.004836082458496, "Time in s": 0.064731 }, { "step": 160, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 5.613172563674658, "RMSE": 10.244365728872303, "R2": -26.67772385659461, "Memory in Mb": 0.004836082458496, "Time in s": 0.079792 }, { "step": 180, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 5.139122523864994, "RMSE": 9.674573881172426, "R2": -20.679349421494624, "Memory in Mb": 0.004836082458496, "Time in s": 0.096247 }, { "step": 200, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 4.970287512907828, "RMSE": 9.286148634805688, "R2": -19.03287536608377, "Memory in Mb": 0.004836082458496, "Time in s": 0.114161 }, { "step": 220, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 4.714509288646119, "RMSE": 8.88589717245386, "R2": -18.78694495096694, "Memory in Mb": 0.004836082458496, "Time in s": 0.133481 }, { "step": 240, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 4.3785831664508095, "RMSE": 8.51169894931726, "R2": -17.292125083299812, "Memory in Mb": 0.004836082458496, "Time in s": 0.154212 }, { "step": 260, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 4.192432902948977, "RMSE": 8.203158141559566, "R2": -16.21895925323482, "Memory in Mb": 0.0049962997436523, "Time in s": 0.176332 }, { "step": 280, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 4.032216676138626, "RMSE": 7.92689648751503, "R2": -15.834209174335763, "Memory in Mb": 0.0049962997436523, "Time in s": 0.199865 }, { "step": 300, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 3.888249411356283, "RMSE": 7.680244711632193, "R2": -14.54126486396457, "Memory in Mb": 0.0049962997436523, "Time in s": 0.224857 }, { "step": 320, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 3.851910342336546, "RMSE": 7.48583024126048, "R2": -14.495465984230798, "Memory in Mb": 0.0049962997436523, "Time in s": 0.251273 }, { "step": 340, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 3.7628843932429423, "RMSE": 7.2990742240635536, "R2": -14.5680671641431, "Memory in Mb": 0.0049962997436523, "Time in s": 0.279095 }, { "step": 360, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 3.741498329747232, "RMSE": 7.147194018854174, "R2": -14.04949995366026, "Memory in Mb": 0.0049962997436523, "Time in s": 0.308317 }, { "step": 380, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 3.6331417160345065, "RMSE": 6.972318267910069, "R2": -13.817498979914417, "Memory in Mb": 0.0049962997436523, "Time in s": 0.3389480000000001 }, { "step": 400, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 3.505723677240456, "RMSE": 6.801269751447825, "R2": -13.497878046830476, "Memory in Mb": 0.0049962997436523, "Time in s": 0.371039 }, { "step": 420, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 3.377789937544477, "RMSE": 6.6406714986639335, "R2": -13.278693194916952, "Memory in Mb": 0.0049962997436523, "Time in s": 0.4045350000000001 }, { "step": 440, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 3.285565585155429, "RMSE": 6.496417025168413, "R2": -12.417819031510929, "Memory in Mb": 0.0049962997436523, "Time in s": 0.4394350000000001 }, { "step": 460, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 3.204438206990859, "RMSE": 6.363151879091182, "R2": -11.207416254643826, "Memory in Mb": 0.0049962997436523, "Time in s": 0.4757300000000001 }, { "step": 480, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 3.1147239220792944, "RMSE": 6.234124280033156, "R2": -10.44779843680249, "Memory in Mb": 0.0049962997436523, "Time in s": 0.5134280000000001 }, { "step": 500, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 3.0674610457420317, "RMSE": 6.126558214637352, "R2": -9.824203383261038, "Memory in Mb": 0.0049962997436523, "Time in s": 0.5525380000000001 }, { "step": 520, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.990407253638538, "RMSE": 6.01302433311803, "R2": -9.444947809169491, "Memory in Mb": 0.0049962997436523, "Time in s": 0.593122 }, { "step": 540, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.9353658306947947, "RMSE": 5.909270916056388, "R2": -9.05064000964308, "Memory in Mb": 0.0049962997436523, "Time in s": 0.635128 }, { "step": 560, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.8633890512526734, "RMSE": 5.806679023039649, "R2": -8.935926541145857, "Memory in Mb": 0.0049962997436523, "Time in s": 0.6785490000000001 }, { "step": 580, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.807495338487497, "RMSE": 5.711109374041071, "R2": -8.849273711490637, "Memory in Mb": 0.0049962997436523, "Time in s": 0.723357 }, { "step": 600, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.7371272959787114, "RMSE": 5.616984296672238, "R2": -8.421904346026553, "Memory in Mb": 0.0049962997436523, "Time in s": 0.769575 }, { "step": 620, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.695279458158905, "RMSE": 5.533794104458184, "R2": -8.005492094038127, "Memory in Mb": 0.0049962997436523, "Time in s": 0.817237 }, { "step": 640, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.663427445960627, "RMSE": 5.457208108806078, "R2": -7.594247452705627, "Memory in Mb": 0.0049962997436523, "Time in s": 0.866263 }, { "step": 660, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.616152871221604, "RMSE": 5.378587544649896, "R2": -7.28837246231315, "Memory in Mb": 0.0049962997436523, "Time in s": 0.916653 }, { "step": 680, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.5798661012588893, "RMSE": 5.305972052989116, "R2": -7.193548818831784, "Memory in Mb": 0.0049962997436523, "Time in s": 0.968481 }, { "step": 700, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.537320459903927, "RMSE": 5.236098928386573, "R2": -7.188742583674767, "Memory in Mb": 0.0049962997436523, "Time in s": 1.021719 }, { "step": 720, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.487562037475977, "RMSE": 5.165214649048708, "R2": -7.14359946989749, "Memory in Mb": 0.0049962997436523, "Time in s": 1.076348 }, { "step": 740, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.4359344014471898, "RMSE": 5.096521995605296, "R2": -6.923665614900413, "Memory in Mb": 0.0049962997436523, "Time in s": 1.1323770000000002 }, { "step": 760, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.407655610747697, "RMSE": 5.035258504842907, "R2": -6.818106944929671, "Memory in Mb": 0.0049962997436523, "Time in s": 1.1897670000000002 }, { "step": 780, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.359216458068109, "RMSE": 4.971257259303496, "R2": -6.65476288050581, "Memory in Mb": 0.0049962997436523, "Time in s": 1.2485520000000003 }, { "step": 800, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.316070029510264, "RMSE": 4.9101929612142525, "R2": -6.535402552442101, "Memory in Mb": 0.0049962997436523, "Time in s": 1.3087800000000005 }, { "step": 820, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.2777366252623445, "RMSE": 4.852446886619337, "R2": -6.440024000118236, "Memory in Mb": 0.0049962997436523, "Time in s": 1.3703650000000005 }, { "step": 840, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.243368105900121, "RMSE": 4.7970088928814505, "R2": -6.33849981001193, "Memory in Mb": 0.0049962997436523, "Time in s": 1.4333480000000005 }, { "step": 860, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.208161873346368, "RMSE": 4.742699334581194, "R2": -6.1609167229990645, "Memory in Mb": 0.0049962997436523, "Time in s": 1.4977110000000002 }, { "step": 880, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.173524312605847, "RMSE": 4.690026300839657, "R2": -5.967944096931786, "Memory in Mb": 0.0049962997436523, "Time in s": 1.5634250000000005 }, { "step": 900, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.143113317062195, "RMSE": 4.639957881226245, "R2": -5.848706397355668, "Memory in Mb": 0.0049962997436523, "Time in s": 1.6305320000000003 }, { "step": 920, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.107662636673197, "RMSE": 4.590154711256589, "R2": -5.812600067991807, "Memory in Mb": 0.0049962997436523, "Time in s": 1.6990770000000004 }, { "step": 940, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.084055644614135, "RMSE": 4.5438188766398575, "R2": -5.732386133187966, "Memory in Mb": 0.0049962997436523, "Time in s": 1.7689810000000004 }, { "step": 960, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.0573225686306618, "RMSE": 4.498049663013517, "R2": -5.666421016566231, "Memory in Mb": 0.0049962997436523, "Time in s": 1.8402960000000004 }, { "step": 980, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 2.029372876222096, "RMSE": 4.453478872426294, "R2": -5.661880798559547, "Memory in Mb": 0.0049962997436523, "Time in s": 1.9129870000000004 }, { "step": 1000, "track": "Regression", "model": "Linear Regression with l2 regularization", "dataset": "TrumpApproval", "MAE": 1.9991816433402003, "RMSE": 4.409973662813209, "R2": -5.642320489885111, "Memory in Mb": 0.0049962997436523, "Time in s": 1.9870360000000005 }, { "step": 11, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 29.34636433128918, "RMSE": 30.877867366178624, "R2": -1226.303892160441, "Memory in Mb": 0.0034055709838867, "Time in s": 0.002755 }, { "step": 22, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 16.78579478575624, "RMSE": 22.219906445728544, "R2": -521.8939460594183, "Memory in Mb": 0.0034055709838867, "Time in s": 0.007689 }, { "step": 33, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 12.764406226748012, "RMSE": 18.43476392899385, "R2": -235.02444355689545, "Memory in Mb": 0.0034055709838867, "Time in s": 0.0139269999999999 }, { "step": 44, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 10.51475037374614, "RMSE": 16.140786164803156, "R2": -204.11441945614396, "Memory in Mb": 0.0034055709838867, "Time in s": 0.021043 }, { "step": 55, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 11.118868381910096, "RMSE": 17.807152193193623, "R2": -60.900579144648304, "Memory in Mb": 0.0034055709838867, "Time in s": 0.0290209999999999 }, { "step": 66, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 10.068652098820438, "RMSE": 16.444921319285292, "R2": -21.75701273895947, "Memory in Mb": 0.0034055709838867, "Time in s": 0.037852 }, { "step": 77, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 9.238561614797426, "RMSE": 15.414518181428049, "R2": -12.40107017683018, "Memory in Mb": 0.0034055709838867, "Time in s": 0.0475289999999999 }, { "step": 88, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 8.397438800335843, "RMSE": 14.475112340817043, "R2": -9.714489831884093, "Memory in Mb": 0.0034055709838867, "Time in s": 0.0580659999999999 }, { "step": 99, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 7.833048644024143, "RMSE": 13.715858800506394, "R2": -7.045954767890709, "Memory in Mb": 0.0034055709838867, "Time in s": 0.069447 }, { "step": 110, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 7.655503029296072, "RMSE": 13.224205829308971, "R2": -4.223044606682061, "Memory in Mb": 0.0034055709838867, "Time in s": 0.0819039999999999 }, { "step": 121, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 7.616633860178707, "RMSE": 12.86945366769748, "R2": -2.809655727072758, "Memory in Mb": 0.0034055709838867, "Time in s": 0.0952199999999999 }, { "step": 132, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 7.226514673025618, "RMSE": 12.359535435581538, "R2": -1.871770505407636, "Memory in Mb": 0.0034055709838867, "Time in s": 0.1094009999999999 }, { "step": 143, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 7.028644030968596, "RMSE": 11.955222747545204, "R2": -1.1763474084194208, "Memory in Mb": 0.0034055709838867, "Time in s": 0.1244559999999999 }, { "step": 154, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 6.986848640780892, "RMSE": 11.69340351574852, "R2": -0.7694704308339801, "Memory in Mb": 0.0034055709838867, "Time in s": 0.1403709999999999 }, { "step": 165, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 7.055944609610511, "RMSE": 11.647997480703344, "R2": -0.411397823157807, "Memory in Mb": 0.0034055709838867, "Time in s": 0.1571089999999999 }, { "step": 176, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 7.165300854035116, "RMSE": 11.69334605191042, "R2": -0.146892755517725, "Memory in Mb": 0.0034055709838867, "Time in s": 0.1746439999999999 }, { "step": 187, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 7.086580322778478, "RMSE": 11.479257625599036, "R2": 0.0950328202686906, "Memory in Mb": 0.0034055709838867, "Time in s": 0.1929879999999999 }, { "step": 198, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 7.0079421524022685, "RMSE": 11.279628541389028, "R2": 0.3049625679809165, "Memory in Mb": 0.0034055709838867, "Time in s": 0.2121359999999999 }, { "step": 209, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 7.136281210496879, "RMSE": 11.437970564343969, "R2": 0.4108328996032877, "Memory in Mb": 0.0034055709838867, "Time in s": 0.2320939999999999 }, { "step": 220, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 7.591733813835971, "RMSE": 12.23821647621677, "R2": 0.409482641430799, "Memory in Mb": 0.0034055709838867, "Time in s": 0.252837 }, { "step": 231, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 7.63642424272378, "RMSE": 12.197368986664095, "R2": 0.4982590675647103, "Memory in Mb": 0.0034055709838867, "Time in s": 0.274371 }, { "step": 242, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 7.775639220351206, "RMSE": 12.334191292520584, "R2": 0.5871659255406134, "Memory in Mb": 0.0034055709838867, "Time in s": 0.296703 }, { "step": 253, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 7.787415018822619, "RMSE": 12.26821713761009, "R2": 0.6452735558950271, "Memory in Mb": 0.0034055709838867, "Time in s": 0.31983 }, { "step": 264, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 8.387229506824328, "RMSE": 13.12794439290609, "R2": 0.6288834273883384, "Memory in Mb": 0.0034589767456054, "Time in s": 0.343762 }, { "step": 275, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 8.893165599265544, "RMSE": 14.22060275652947, "R2": 0.6168153604937621, "Memory in Mb": 0.0034589767456054, "Time in s": 0.368493 }, { "step": 286, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 9.145334455404228, "RMSE": 14.488680433063887, "R2": 0.6554856011642076, "Memory in Mb": 0.0034589767456054, "Time in s": 0.394025 }, { "step": 297, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 9.138984650870034, "RMSE": 14.40937364029996, "R2": 0.7044680409221951, "Memory in Mb": 0.0034589767456054, "Time in s": 0.420371 }, { "step": 308, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 9.653721426872565, "RMSE": 15.186897141025446, "R2": 0.7076222812215553, "Memory in Mb": 0.0034589767456054, "Time in s": 0.447515 }, { "step": 319, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 10.688547371510406, "RMSE": 17.568442046558065, "R2": 0.6449394075517852, "Memory in Mb": 0.0034589767456054, "Time in s": 0.475457 }, { "step": 330, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 11.136888804773204, "RMSE": 18.130051576409294, "R2": 0.6764089203981734, "Memory in Mb": 0.0034589767456054, "Time in s": 0.5041950000000001 }, { "step": 341, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 11.389709627918275, "RMSE": 18.31814497212097, "R2": 0.7041960757214223, "Memory in Mb": 0.0034589767456054, "Time in s": 0.53373 }, { "step": 352, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 11.506556624125665, "RMSE": 18.357319157972537, "R2": 0.7299499902857889, "Memory in Mb": 0.0034589767456054, "Time in s": 0.56408 }, { "step": 363, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 12.507799925411486, "RMSE": 19.94157204039453, "R2": 0.6905532928077196, "Memory in Mb": 0.0034589767456054, "Time in s": 0.5952430000000001 }, { "step": 374, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 13.00643913732256, "RMSE": 20.915910426515573, "R2": 0.6870553798396234, "Memory in Mb": 0.0034589767456054, "Time in s": 0.6272240000000001 }, { "step": 385, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 13.44126440090726, "RMSE": 21.59107831138786, "R2": 0.7049595304644938, "Memory in Mb": 0.0034589767456054, "Time in s": 0.6600050000000001 }, { "step": 396, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 13.452600873244052, "RMSE": 21.4799043653453, "R2": 0.7277322681469997, "Memory in Mb": 0.0034589767456054, "Time in s": 0.6935880000000001 }, { "step": 407, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 14.30954893105116, "RMSE": 22.795153034451378, "R2": 0.7149787127692513, "Memory in Mb": 0.0034589767456054, "Time in s": 0.7279810000000001 }, { "step": 418, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 15.058465273046648, "RMSE": 24.12824896117789, "R2": 0.7002387244037227, "Memory in Mb": 0.0034589767456054, "Time in s": 0.7631730000000001 }, { "step": 429, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 15.61316127520364, "RMSE": 25.00709438423813, "R2": 0.7138656442877266, "Memory in Mb": 0.0034589767456054, "Time in s": 0.799166 }, { "step": 440, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 15.833192306896644, "RMSE": 25.159785721055627, "R2": 0.7308613212218023, "Memory in Mb": 0.0034589767456054, "Time in s": 0.8359580000000001 }, { "step": 451, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 16.36714766376461, "RMSE": 25.770608582556893, "R2": 0.729638089688956, "Memory in Mb": 0.0034589767456054, "Time in s": 0.87355 }, { "step": 462, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 17.39003054773241, "RMSE": 27.77320733878432, "R2": 0.7050560764454472, "Memory in Mb": 0.0034589767456054, "Time in s": 0.911945 }, { "step": 473, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 18.288428268963266, "RMSE": 29.396681708172505, "R2": 0.7082265052542642, "Memory in Mb": 0.0034589767456054, "Time in s": 0.951137 }, { "step": 484, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 18.65703381705754, "RMSE": 29.64739580601693, "R2": 0.7194912595024185, "Memory in Mb": 0.0034589767456054, "Time in s": 0.991127 }, { "step": 495, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 19.170202167844984, "RMSE": 30.22319045197901, "R2": 0.7257784495510498, "Memory in Mb": 0.0034589767456054, "Time in s": 1.031919 }, { "step": 506, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 20.00164363454025, "RMSE": 31.52072905752619, "R2": 0.7103967314785831, "Memory in Mb": 0.0034589767456054, "Time in s": 1.073505 }, { "step": 517, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 20.7279777099298, "RMSE": 32.51187613530653, "R2": 0.7092492864364832, "Memory in Mb": 0.0034589767456054, "Time in s": 1.115928 }, { "step": 528, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 21.56683033620196, "RMSE": 33.84128388534863, "R2": 0.7167757554755416, "Memory in Mb": 0.0034589767456054, "Time in s": 1.159144 }, { "step": 539, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 21.76383497583081, "RMSE": 33.92033428284125, "R2": 0.727201090633804, "Memory in Mb": 0.0034589767456054, "Time in s": 1.203152 }, { "step": 550, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 22.69913149057359, "RMSE": 35.42417858076478, "R2": 0.7116454901231712, "Memory in Mb": 0.0034589767456054, "Time in s": 1.247925 }, { "step": 561, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 23.377380034069706, "RMSE": 36.32705612571005, "R2": 0.7100204288247138, "Memory in Mb": 0.0034589767456054, "Time in s": 1.293462 }, { "step": 572, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "ChickWeights", "MAE": 24.23392939046311, "RMSE": 37.557568322570944, "R2": 0.7132890208408607, "Memory in Mb": 0.0034589767456054, "Time in s": 1.339772 }, { "step": 20, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 19.88769754963664, "RMSE": 24.32970381980572, "R2": -1387.4429851591376, "Memory in Mb": 0.0043020248413085, "Time in s": 0.004188 }, { "step": 40, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 13.670966252574736, "RMSE": 18.65150015508889, "R2": -138.85979610511808, "Memory in Mb": 0.0043020248413085, "Time in s": 0.011118 }, { "step": 60, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 10.92834996141842, "RMSE": 15.667746469337834, "R2": -132.052589810652, "Memory in Mb": 0.0043020248413085, "Time in s": 0.019635 }, { "step": 80, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 9.678171261463673, "RMSE": 14.124417656525663, "R2": -107.46634425227307, "Memory in Mb": 0.0043020248413085, "Time in s": 0.0297069999999999 }, { "step": 100, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 9.352313294103828, "RMSE": 13.38210191485773, "R2": -60.090321390572015, "Memory in Mb": 0.0043020248413085, "Time in s": 0.041437 }, { "step": 120, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 8.620142702346234, "RMSE": 12.447697479286916, "R2": -43.84064485890953, "Memory in Mb": 0.0043020248413085, "Time in s": 0.05473 }, { "step": 140, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 8.069393725677067, "RMSE": 11.747669450243144, "R2": -40.272086023690846, "Memory in Mb": 0.0043020248413085, "Time in s": 0.069574 }, { "step": 160, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 7.915997483818508, "RMSE": 11.323556682786094, "R2": -32.81628847194888, "Memory in Mb": 0.0043020248413085, "Time in s": 0.085987 }, { "step": 180, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 7.901057285338727, "RMSE": 11.048721851620664, "R2": -27.27526182903414, "Memory in Mb": 0.0043020248413085, "Time in s": 0.103947 }, { "step": 200, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 7.54356570823564, "RMSE": 10.615481381947994, "R2": -25.17890116869019, "Memory in Mb": 0.0043020248413085, "Time in s": 0.1235479999999999 }, { "step": 220, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 7.241521693861677, "RMSE": 10.231227443733497, "R2": -25.232015334984823, "Memory in Mb": 0.0043020248413085, "Time in s": 0.1447119999999999 }, { "step": 240, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 7.008192421558015, "RMSE": 9.935910620042463, "R2": -23.925679436807183, "Memory in Mb": 0.0043020248413085, "Time in s": 0.1674199999999999 }, { "step": 260, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 6.801990869552961, "RMSE": 9.666795781283112, "R2": -22.91166502123009, "Memory in Mb": 0.0044355392456054, "Time in s": 0.191681 }, { "step": 280, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 6.624313646675292, "RMSE": 9.422664085622769, "R2": -22.786676328633025, "Memory in Mb": 0.0044355392456054, "Time in s": 0.217492 }, { "step": 300, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 6.459069309379183, "RMSE": 9.212027904845302, "R2": -21.358709628275356, "Memory in Mb": 0.0044355392456054, "Time in s": 0.244937 }, { "step": 320, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 6.271769455500056, "RMSE": 8.978276576497144, "R2": -21.290029949269996, "Memory in Mb": 0.0044355392456054, "Time in s": 0.2739479999999999 }, { "step": 340, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 6.106653016686588, "RMSE": 8.760106381933458, "R2": -21.42424847489592, "Memory in Mb": 0.0044355392456054, "Time in s": 0.304509 }, { "step": 360, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.987363514041657, "RMSE": 8.573066448421043, "R2": -20.653260781415117, "Memory in Mb": 0.0044355392456054, "Time in s": 0.336642 }, { "step": 380, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.8616356212919145, "RMSE": 8.393806584529749, "R2": -20.475259224624704, "Memory in Mb": 0.0044355392456054, "Time in s": 0.370328 }, { "step": 400, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.709779552257037, "RMSE": 8.216191215364908, "R2": -20.15755692495403, "Memory in Mb": 0.0044355392456054, "Time in s": 0.4056389999999999 }, { "step": 420, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.611842526965273, "RMSE": 8.072589482864162, "R2": -20.100376445858966, "Memory in Mb": 0.0044355392456054, "Time in s": 0.442509 }, { "step": 440, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.621266668644241, "RMSE": 8.061169250733263, "R2": -19.659995268253144, "Memory in Mb": 0.0044355392456054, "Time in s": 0.480923 }, { "step": 460, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.589374981160082, "RMSE": 7.977922595195435, "R2": -18.1892858176961, "Memory in Mb": 0.0044355392456054, "Time in s": 0.520896 }, { "step": 480, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.601949193869223, "RMSE": 7.939757215258646, "R2": -17.568871361729258, "Memory in Mb": 0.0044355392456054, "Time in s": 0.5624170000000001 }, { "step": 500, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.5323381947357735, "RMSE": 7.827118471157092, "R2": -16.667155417363553, "Memory in Mb": 0.0044355392456054, "Time in s": 0.6055100000000001 }, { "step": 520, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.482642323931563, "RMSE": 7.735647602994712, "R2": -16.286764124140948, "Memory in Mb": 0.0044355392456054, "Time in s": 0.6502260000000001 }, { "step": 540, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.40625682094428, "RMSE": 7.63238246035087, "R2": -15.7666448554263, "Memory in Mb": 0.0044355392456054, "Time in s": 0.696447 }, { "step": 560, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.339029679572209, "RMSE": 7.532223621796607, "R2": -15.718570546376949, "Memory in Mb": 0.0044355392456054, "Time in s": 0.744222 }, { "step": 580, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.278136676956568, "RMSE": 7.444054065699633, "R2": -15.733326658615429, "Memory in Mb": 0.0044355392456054, "Time in s": 0.7935180000000001 }, { "step": 600, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.267448053107655, "RMSE": 7.406286860836784, "R2": -15.380732931295814, "Memory in Mb": 0.0044355392456054, "Time in s": 0.8443630000000001 }, { "step": 620, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.236749685364014, "RMSE": 7.349650271122191, "R2": -14.88527744664384, "Memory in Mb": 0.0044355392456054, "Time in s": 0.8968030000000001 }, { "step": 640, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.212060707085285, "RMSE": 7.303465599867649, "R2": -14.393054201831111, "Memory in Mb": 0.0044355392456054, "Time in s": 0.95074 }, { "step": 660, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.169763730821092, "RMSE": 7.239859498572405, "R2": -14.017341318649356, "Memory in Mb": 0.0044355392456054, "Time in s": 1.0062160000000002 }, { "step": 680, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.126488999027155, "RMSE": 7.167741867944588, "R2": -13.952260083042017, "Memory in Mb": 0.0044355392456054, "Time in s": 1.063227 }, { "step": 700, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.093088048073085, "RMSE": 7.110044108134988, "R2": -14.098928285386927, "Memory in Mb": 0.0044355392456054, "Time in s": 1.121789 }, { "step": 720, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.090740367293551, "RMSE": 7.074302078930798, "R2": -14.275901824522656, "Memory in Mb": 0.0044355392456054, "Time in s": 1.181923 }, { "step": 740, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.094807885255693, "RMSE": 7.045283722404726, "R2": -14.141723406350016, "Memory in Mb": 0.0044355392456054, "Time in s": 1.243554 }, { "step": 760, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.043787658869922, "RMSE": 6.975646542541488, "R2": -14.00468895273832, "Memory in Mb": 0.0044355392456054, "Time in s": 1.306712 }, { "step": 780, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.064043270517397, "RMSE": 6.970645877797938, "R2": -14.050305184338798, "Memory in Mb": 0.0044355392456054, "Time in s": 1.3714110000000002 }, { "step": 800, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.100755566375936, "RMSE": 7.010389089224324, "R2": -14.360083784619212, "Memory in Mb": 0.0044355392456054, "Time in s": 1.4376520000000002 }, { "step": 820, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.088064827359337, "RMSE": 6.979627415872227, "R2": -14.392786134873418, "Memory in Mb": 0.0044355392456054, "Time in s": 1.505445 }, { "step": 840, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.068856460674791, "RMSE": 6.93736545783203, "R2": -14.348127111309871, "Memory in Mb": 0.0044355392456054, "Time in s": 1.574755 }, { "step": 860, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.054699520351681, "RMSE": 6.900248160625591, "R2": -14.158172906563095, "Memory in Mb": 0.0044355392456054, "Time in s": 1.645553 }, { "step": 880, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.051365258335469, "RMSE": 6.881479694679562, "R2": -14.000915574481752, "Memory in Mb": 0.0044355392456054, "Time in s": 1.717914 }, { "step": 900, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 5.025346349320704, "RMSE": 6.842894221251935, "R2": -13.895672840614656, "Memory in Mb": 0.0044355392456054, "Time in s": 1.791764 }, { "step": 920, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 4.9962011230931616, "RMSE": 6.800765764747934, "R2": -13.95456831471299, "Memory in Mb": 0.0044355392456054, "Time in s": 1.867216 }, { "step": 940, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 4.964612353038952, "RMSE": 6.764345134580912, "R2": -13.920332812605436, "Memory in Mb": 0.0044355392456054, "Time in s": 1.944198 }, { "step": 960, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 4.9296416909632255, "RMSE": 6.717192667284049, "R2": -13.866880687662514, "Memory in Mb": 0.0044355392456054, "Time in s": 2.02269 }, { "step": 980, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 4.910978624057615, "RMSE": 6.682715130965835, "R2": -14.000438748691009, "Memory in Mb": 0.0044355392456054, "Time in s": 2.102738 }, { "step": 1000, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 1", "dataset": "TrumpApproval", "MAE": 4.906394390750375, "RMSE": 6.665596501187553, "R2": -14.174901311798424, "Memory in Mb": 0.0044355392456054, "Time in s": 2.184247 }, { "step": 11, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 40.361343182089286, "RMSE": 50.93510711941157, "R2": -3338.580868182736, "Memory in Mb": 0.0034055709838867, "Time in s": 0.003338 }, { "step": 22, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 33.77268754890631, "RMSE": 41.67984599422324, "R2": -1838.845575618055, "Memory in Mb": 0.0034055709838867, "Time in s": 0.00919 }, { "step": 33, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 32.39258875507137, "RMSE": 38.96806999674433, "R2": -1053.6287703611629, "Memory in Mb": 0.0034055709838867, "Time in s": 0.01639 }, { "step": 44, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 30.94881031854868, "RMSE": 36.76152485506615, "R2": -1062.9809670274265, "Memory in Mb": 0.0034055709838867, "Time in s": 0.024921 }, { "step": 55, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 33.955857035779495, "RMSE": 41.369655851763525, "R2": -333.094700988151, "Memory in Mb": 0.0034055709838867, "Time in s": 0.034827 }, { "step": 66, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 34.010493836145145, "RMSE": 40.92418807176112, "R2": -139.93270784533922, "Memory in Mb": 0.0034055709838867, "Time in s": 0.046059 }, { "step": 77, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 34.064338631511326, "RMSE": 40.5595538563462, "R2": -91.78246602216656, "Memory in Mb": 0.0034055709838867, "Time in s": 0.058629 }, { "step": 88, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 34.363478110253816, "RMSE": 40.47408671194747, "R2": -82.76869054449229, "Memory in Mb": 0.0034055709838867, "Time in s": 0.072516 }, { "step": 99, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 34.108671766629826, "RMSE": 39.953033914579606, "R2": -67.2701887367714, "Memory in Mb": 0.0034055709838867, "Time in s": 0.087732 }, { "step": 110, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 35.5272246808861, "RMSE": 41.29414928968925, "R2": -49.9285816695273, "Memory in Mb": 0.0034055709838867, "Time in s": 0.104612 }, { "step": 121, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 35.85052464333277, "RMSE": 41.48724749727828, "R2": -38.59084342971371, "Memory in Mb": 0.0034055709838867, "Time in s": 0.122819 }, { "step": 132, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 36.414238795248615, "RMSE": 42.10793271457587, "R2": -32.332913655998325, "Memory in Mb": 0.0034055709838867, "Time in s": 0.142364 }, { "step": 143, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 37.27092918309872, "RMSE": 43.0841670883325, "R2": -27.26495387953688, "Memory in Mb": 0.0034055709838867, "Time in s": 0.163229 }, { "step": 154, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 37.68834060456834, "RMSE": 43.351809236536255, "R2": -23.3206899065102, "Memory in Mb": 0.0034055709838867, "Time in s": 0.18538 }, { "step": 165, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 37.63751931524077, "RMSE": 43.32469674855668, "R2": -18.52621065458175, "Memory in Mb": 0.0034055709838867, "Time in s": 0.208847 }, { "step": 176, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 38.77878602757167, "RMSE": 44.74953718825682, "R2": -15.796635622291838, "Memory in Mb": 0.0034055709838867, "Time in s": 0.233634 }, { "step": 187, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 39.47954967522975, "RMSE": 45.39032172466195, "R2": -13.149195443978996, "Memory in Mb": 0.0034055709838867, "Time in s": 0.259707 }, { "step": 198, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 40.91548075261064, "RMSE": 46.96428169788168, "R2": -11.049082215962626, "Memory in Mb": 0.0034055709838867, "Time in s": 0.287109 }, { "step": 209, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 41.53723737741547, "RMSE": 47.716579905431935, "R2": -9.253665706385002, "Memory in Mb": 0.0034055709838867, "Time in s": 0.31584 }, { "step": 220, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 41.99935380922626, "RMSE": 48.63121942098776, "R2": -8.324525171754294, "Memory in Mb": 0.0034055709838867, "Time in s": 0.345843 }, { "step": 231, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 42.76794868726854, "RMSE": 49.65880643089243, "R2": -7.316484115890946, "Memory in Mb": 0.0034055709838867, "Time in s": 0.377141 }, { "step": 242, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 44.368299619960766, "RMSE": 51.88245138837915, "R2": -6.304578357179455, "Memory in Mb": 0.0034055709838867, "Time in s": 0.409767 }, { "step": 253, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 45.426835880148886, "RMSE": 53.192808855117775, "R2": -5.668628208432534, "Memory in Mb": 0.0034055709838867, "Time in s": 0.443674 }, { "step": 264, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 46.93737170570451, "RMSE": 55.9021194350506, "R2": -5.729354993233594, "Memory in Mb": 0.0034589767456054, "Time in s": 0.478844 }, { "step": 275, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 48.507353400069945, "RMSE": 58.8434937271261, "R2": -5.560984055006233, "Memory in Mb": 0.0034589767456054, "Time in s": 0.515365 }, { "step": 286, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 49.83788736782816, "RMSE": 60.74084767697289, "R2": -5.054961799673954, "Memory in Mb": 0.0034589767456054, "Time in s": 0.5532039999999999 }, { "step": 297, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 51.62361105051165, "RMSE": 63.27455882125991, "R2": -4.698656745997159, "Memory in Mb": 0.0034589767456054, "Time in s": 0.5923289999999999 }, { "step": 308, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 53.1847087657747, "RMSE": 65.32139627595005, "R2": -4.409001340116382, "Memory in Mb": 0.0034589767456054, "Time in s": 0.6328059999999999 }, { "step": 319, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 55.18568520771326, "RMSE": 70.36874449488667, "R2": -4.696335728503607, "Memory in Mb": 0.0034589767456054, "Time in s": 0.6746009999999999 }, { "step": 330, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 56.89081675494835, "RMSE": 72.51519786174504, "R2": -4.176742159590063, "Memory in Mb": 0.0034589767456054, "Time in s": 0.7176629999999999 }, { "step": 341, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 58.741890997125225, "RMSE": 75.13624143509449, "R2": -3.976681879584251, "Memory in Mb": 0.0034589767456054, "Time in s": 0.7620199999999999 }, { "step": 352, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 60.2425190521958, "RMSE": 76.8261590755005, "R2": -3.729812475420129, "Memory in Mb": 0.0034589767456054, "Time in s": 0.8076819999999999 }, { "step": 363, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 62.22918871806441, "RMSE": 80.45649530418282, "R2": -4.037201263859445, "Memory in Mb": 0.0034589767456054, "Time in s": 0.854609 }, { "step": 374, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 64.15805403621584, "RMSE": 84.29062360683722, "R2": -4.082442538013045, "Memory in Mb": 0.0034589767456054, "Time in s": 0.902845 }, { "step": 385, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 65.35464556519459, "RMSE": 85.58979700811152, "R2": -3.6363575203718743, "Memory in Mb": 0.0034589767456054, "Time in s": 0.952397 }, { "step": 396, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 67.08652533638559, "RMSE": 87.70251677464411, "R2": -3.538952097004609, "Memory in Mb": 0.0034589767456054, "Time in s": 1.00322 }, { "step": 407, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 68.34565949899115, "RMSE": 89.3540667816312, "R2": -3.3794635851122994, "Memory in Mb": 0.0034589767456054, "Time in s": 1.055319 }, { "step": 418, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 70.95506872236689, "RMSE": 94.70758550832085, "R2": -3.618420231648276, "Memory in Mb": 0.0034589767456054, "Time in s": 1.108722 }, { "step": 429, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 72.57879663609631, "RMSE": 96.822819417077, "R2": -3.2894241164712765, "Memory in Mb": 0.0034589767456054, "Time in s": 1.163438 }, { "step": 440, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 74.40667828471298, "RMSE": 99.12463362784464, "R2": -3.1775863007897582, "Memory in Mb": 0.0034589767456054, "Time in s": 1.219419 }, { "step": 451, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 75.93202948942836, "RMSE": 101.47969042740628, "R2": -3.192319994595937, "Memory in Mb": 0.0034589767456054, "Time in s": 1.276691 }, { "step": 462, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 78.59712471455953, "RMSE": 106.68213481552291, "R2": -3.3518185198786687, "Memory in Mb": 0.0034589767456054, "Time in s": 1.335258 }, { "step": 473, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 81.70573920737151, "RMSE": 112.24508574603004, "R2": -3.253866822086197, "Memory in Mb": 0.0034589767456054, "Time in s": 1.395089 }, { "step": 484, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 82.72251416230137, "RMSE": 113.16810597159808, "R2": -3.0871576545332315, "Memory in Mb": 0.0034589767456054, "Time in s": 1.456215 }, { "step": 495, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 84.44211178292737, "RMSE": 115.99711612480068, "R2": -3.039385949207989, "Memory in Mb": 0.0034589767456054, "Time in s": 1.518639 }, { "step": 506, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 86.55149997089892, "RMSE": 119.94151559804617, "R2": -3.193242857597108, "Memory in Mb": 0.0034589767456054, "Time in s": 1.582321 }, { "step": 517, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 87.81070722823603, "RMSE": 121.26627191062052, "R2": -3.0449837234699952, "Memory in Mb": 0.0034589767456054, "Time in s": 1.64731 }, { "step": 528, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 90.44199567451936, "RMSE": 126.238673662019, "R2": -2.9411377147279807, "Memory in Mb": 0.0034589767456054, "Time in s": 1.713605 }, { "step": 539, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 91.59067370330054, "RMSE": 127.24192286613216, "R2": -2.8386881284150203, "Memory in Mb": 0.0034589767456054, "Time in s": 1.781138 }, { "step": 550, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 93.78609063040562, "RMSE": 130.999704877259, "R2": -2.943372518937519, "Memory in Mb": 0.0034589767456054, "Time in s": 1.84997 }, { "step": 561, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 96.49865979675556, "RMSE": 135.93192637304293, "R2": -3.060223463970532, "Memory in Mb": 0.0034589767456054, "Time in s": 1.920139 }, { "step": 572, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "ChickWeights", "MAE": 99.56805853722273, "RMSE": 141.40025114882988, "R2": -3.0639630782357843, "Memory in Mb": 0.0034589767456054, "Time in s": 1.991547 }, { "step": 20, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 38.256966119949794, "RMSE": 53.46437671117289, "R2": -6703.762875072117, "Memory in Mb": 0.0043020248413085, "Time in s": 0.004258 }, { "step": 40, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 36.86518407094958, "RMSE": 46.91757933405302, "R2": -883.9863015306486, "Memory in Mb": 0.0043020248413085, "Time in s": 0.0112559999999999 }, { "step": 60, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 34.81538726709292, "RMSE": 43.77024226536395, "R2": -1037.408328049847, "Memory in Mb": 0.0043020248413085, "Time in s": 0.019887 }, { "step": 80, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 32.82099099523828, "RMSE": 40.95636211937148, "R2": -911.003802678922, "Memory in Mb": 0.0043020248413085, "Time in s": 0.0300789999999999 }, { "step": 100, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 32.41507697560151, "RMSE": 39.67328525303196, "R2": -535.9329715822871, "Memory in Mb": 0.0043020248413085, "Time in s": 0.041942 }, { "step": 120, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 32.126533810299065, "RMSE": 38.74392424963554, "R2": -433.4111998192701, "Memory in Mb": 0.0043020248413085, "Time in s": 0.055368 }, { "step": 140, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.578696449953306, "RMSE": 37.792227545537656, "R2": -426.12792465890055, "Memory in Mb": 0.0043020248413085, "Time in s": 0.070349 }, { "step": 160, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 30.74326128631808, "RMSE": 36.75147996394125, "R2": -355.2131008927076, "Memory in Mb": 0.0043020248413085, "Time in s": 0.086898 }, { "step": 180, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 30.01457804514465, "RMSE": 35.792387341570375, "R2": -295.7316609698654, "Memory in Mb": 0.0043020248413085, "Time in s": 0.104998 }, { "step": 200, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 29.69358993814741, "RMSE": 35.287452593511624, "R2": -288.27615949420783, "Memory in Mb": 0.0043020248413085, "Time in s": 0.124741 }, { "step": 220, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 29.653103799764548, "RMSE": 34.981694493871686, "R2": -305.6605175079266, "Memory in Mb": 0.0043020248413085, "Time in s": 0.146064 }, { "step": 240, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 29.438535707776744, "RMSE": 34.575414655319626, "R2": -300.8328104705327, "Memory in Mb": 0.0043020248413085, "Time in s": 0.168934 }, { "step": 260, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 29.47891951475184, "RMSE": 34.56744094622709, "R2": -304.7589578451177, "Memory in Mb": 0.0044355392456054, "Time in s": 0.193372 }, { "step": 280, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 29.26309099262944, "RMSE": 34.21824031120625, "R2": -312.6907330516863, "Memory in Mb": 0.0044355392456054, "Time in s": 0.2193709999999999 }, { "step": 300, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 29.22587791049338, "RMSE": 34.04470159277256, "R2": -304.37628668920115, "Memory in Mb": 0.0044355392456054, "Time in s": 0.246997 }, { "step": 320, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 29.39018713755992, "RMSE": 34.027497016659055, "R2": -319.1729973057711, "Memory in Mb": 0.0044355392456054, "Time in s": 0.276184 }, { "step": 340, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 29.42027037377748, "RMSE": 33.93053373578466, "R2": -335.4190027425263, "Memory in Mb": 0.0044355392456054, "Time in s": 0.306921 }, { "step": 360, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 29.664307062669348, "RMSE": 34.045635299267715, "R2": -340.48671423689984, "Memory in Mb": 0.0044355392456054, "Time in s": 0.339233 }, { "step": 380, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 29.83498723746747, "RMSE": 34.11808971579651, "R2": -353.80514851974, "Memory in Mb": 0.0044355392456054, "Time in s": 0.373101 }, { "step": 400, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 30.001082895685222, "RMSE": 34.17628998525774, "R2": -365.0785427385626, "Memory in Mb": 0.0044355392456054, "Time in s": 0.408596 }, { "step": 420, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 30.14554243966483, "RMSE": 34.20268208319664, "R2": -377.7780423674053, "Memory in Mb": 0.0044355392456054, "Time in s": 0.445652 }, { "step": 440, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 30.318997649838, "RMSE": 34.29163258825692, "R2": -372.8612574130533, "Memory in Mb": 0.0044355392456054, "Time in s": 0.484259 }, { "step": 460, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 30.44816166194883, "RMSE": 34.34474274542465, "R2": -354.6310813895727, "Memory in Mb": 0.0044355392456054, "Time in s": 0.524426 }, { "step": 480, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 30.547707035634, "RMSE": 34.3460988289287, "R2": -346.476863625336, "Memory in Mb": 0.0044355392456054, "Time in s": 0.5661419999999999 }, { "step": 500, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 30.677713278160866, "RMSE": 34.40102042286509, "R2": -340.27577766039445, "Memory in Mb": 0.0044355392456054, "Time in s": 0.6094289999999999 }, { "step": 520, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 30.774567489967996, "RMSE": 34.41616981796676, "R2": -341.1727526506248, "Memory in Mb": 0.0044355392456054, "Time in s": 0.6543389999999999 }, { "step": 540, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 30.8774276068303, "RMSE": 34.45885995564912, "R2": -340.7651110108783, "Memory in Mb": 0.0044355392456054, "Time in s": 0.7007559999999999 }, { "step": 560, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 30.809160821418956, "RMSE": 34.35467967149731, "R2": -346.7959646189386, "Memory in Mb": 0.0044355392456054, "Time in s": 0.7487349999999999 }, { "step": 580, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 30.794626934327955, "RMSE": 34.31319945532044, "R2": -354.5377185045104, "Memory in Mb": 0.0044355392456054, "Time in s": 0.798249 }, { "step": 600, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 30.95165244409411, "RMSE": 34.41180694760753, "R2": -352.62847406429205, "Memory in Mb": 0.0044355392456054, "Time in s": 0.849322 }, { "step": 620, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.05924245979316, "RMSE": 34.47559777081781, "R2": -348.53049085374005, "Memory in Mb": 0.0044355392456054, "Time in s": 0.901986 }, { "step": 640, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.17486346702509, "RMSE": 34.55495775749415, "R2": -343.578007451748, "Memory in Mb": 0.0044355392456054, "Time in s": 0.956154 }, { "step": 660, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.18138785276698, "RMSE": 34.53217565702543, "R2": -340.6493968041527, "Memory in Mb": 0.0044355392456054, "Time in s": 1.011873 }, { "step": 680, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.262098564397714, "RMSE": 34.57860649898553, "R2": -346.98225985471817, "Memory in Mb": 0.0044355392456054, "Time in s": 1.06915 }, { "step": 700, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.21351117376332, "RMSE": 34.56642775102796, "R2": -355.8704038677769, "Memory in Mb": 0.0044355392456054, "Time in s": 1.127995 }, { "step": 720, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.187412408778744, "RMSE": 34.52480046664081, "R2": -362.8329367085535, "Memory in Mb": 0.0044355392456054, "Time in s": 1.188423 }, { "step": 740, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.11951946368673, "RMSE": 34.44075758421072, "R2": -360.84595808308967, "Memory in Mb": 0.0044355392456054, "Time in s": 1.250358 }, { "step": 760, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.06286774404838, "RMSE": 34.392033812715184, "R2": -363.7319274626152, "Memory in Mb": 0.0044355392456054, "Time in s": 1.313829 }, { "step": 780, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.122129081397333, "RMSE": 34.4147077867913, "R2": -365.8490836115921, "Memory in Mb": 0.0044355392456054, "Time in s": 1.378848 }, { "step": 800, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.106214253085103, "RMSE": 34.39160753515401, "R2": -368.6700713862459, "Memory in Mb": 0.0044355392456054, "Time in s": 1.445416 }, { "step": 820, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.221689813214, "RMSE": 34.48240321448139, "R2": -374.7057202811433, "Memory in Mb": 0.0044355392456054, "Time in s": 1.513551 }, { "step": 840, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.279425902447173, "RMSE": 34.50697415799086, "R2": -378.7344488771949, "Memory in Mb": 0.0044355392456054, "Time in s": 1.583215 }, { "step": 860, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.342876956175303, "RMSE": 34.54160049479585, "R2": -378.8414458535583, "Memory in Mb": 0.0044355392456054, "Time in s": 1.65438 }, { "step": 880, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.26946109805924, "RMSE": 34.463329541799936, "R2": -375.2431199026635, "Memory in Mb": 0.0044355392456054, "Time in s": 1.727121 }, { "step": 900, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.252963502360984, "RMSE": 34.437602544585566, "R2": -376.2648040183398, "Memory in Mb": 0.0044355392456054, "Time in s": 1.801358 }, { "step": 920, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.17140034618248, "RMSE": 34.35879469425013, "R2": -380.710483609337, "Memory in Mb": 0.0044355392456054, "Time in s": 1.877212 }, { "step": 940, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.028682196255257, "RMSE": 34.23221645186374, "R2": -381.1175926718204, "Memory in Mb": 0.0044355392456054, "Time in s": 1.954607 }, { "step": 960, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.091829199349828, "RMSE": 34.349474902309865, "R2": -387.76257537598985, "Memory in Mb": 0.0044355392456054, "Time in s": 2.033516 }, { "step": 980, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.00094350988743, "RMSE": 34.303507421677764, "R2": -394.25294990859175, "Memory in Mb": 0.0044355392456054, "Time in s": 2.113994 }, { "step": 1000, "track": "Regression", "model": "Passive-Aggressive Regressor, mode 2", "dataset": "TrumpApproval", "MAE": 31.128814077399102, "RMSE": 34.425663215951964, "R2": -403.7738674316034, "Memory in Mb": 0.0044355392456054, "Time in s": 2.195941 }, { "step": 11, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 4.6439393939393945, "RMSE": 12.708027567111456, "R2": -206.8805289598106, "Memory in Mb": 0.007791519165039, "Time in s": 0.002301 }, { "step": 22, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 2.7674242424242426, "RMSE": 9.021574170013263, "R2": -85.19732920009746, "Memory in Mb": 0.0116405487060546, "Time in s": 0.007035 }, { "step": 33, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 2.366161616161617, "RMSE": 7.437810062008745, "R2": -37.42129411139464, "Memory in Mb": 0.0161724090576171, "Time in s": 0.013843 }, { "step": 44, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 2.015530303030304, "RMSE": 6.463663489621867, "R2": -31.893061768560024, "Memory in Mb": 0.0202007293701171, "Time in s": 0.022662 }, { "step": 55, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 2.2124242424242424, "RMSE": 6.080421054665558, "R2": -6.217272109648366, "Memory in Mb": 0.0243968963623046, "Time in s": 0.033503 }, { "step": 66, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 2.280050505050505, "RMSE": 5.694858940322259, "R2": -1.7290883479828647, "Memory in Mb": 0.0287837982177734, "Time in s": 0.046733 }, { "step": 77, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 2.61926406926407, "RMSE": 5.707950266794224, "R2": -0.8375532519268223, "Memory in Mb": 0.0331974029541015, "Time in s": 0.062616 }, { "step": 88, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 2.530492424242425, "RMSE": 5.412982721609634, "R2": -0.4983072905775765, "Memory in Mb": 0.0375041961669921, "Time in s": 0.081466 }, { "step": 99, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 2.4755892255892267, "RMSE": 5.17010990945742, "R2": -0.1432234574096695, "Memory in Mb": 0.0422878265380859, "Time in s": 0.103593 }, { "step": 110, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 2.7716666666666683, "RMSE": 5.296236752390676, "R2": 0.1622405877971293, "Memory in Mb": 0.0433177947998046, "Time in s": 0.129424 }, { "step": 121, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 3.180853994490359, "RMSE": 5.621206607854847, "R2": 0.2731837882445769, "Memory in Mb": 0.0438785552978515, "Time in s": 0.158775 }, { "step": 132, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 3.3642676767676765, "RMSE": 5.706770043255583, "R2": 0.3877536814355664, "Memory in Mb": 0.0436267852783203, "Time in s": 0.191664 }, { "step": 143, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 3.646736596736596, "RMSE": 5.919243012407738, "R2": 0.4664867393310171, "Memory in Mb": 0.0439319610595703, "Time in s": 0.228099 }, { "step": 154, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 3.7550865800865783, "RMSE": 5.97572666401829, "R2": 0.537892640768072, "Memory in Mb": 0.0440692901611328, "Time in s": 0.268063 }, { "step": 165, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 4.093838383838381, "RMSE": 6.488494998076776, "R2": 0.562039588096868, "Memory in Mb": 0.0446529388427734, "Time in s": 0.311593 }, { "step": 176, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 4.458428030303029, "RMSE": 6.947478945595657, "R2": 0.5951448357515823, "Memory in Mb": 0.0446796417236328, "Time in s": 0.358632 }, { "step": 187, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 4.792959001782529, "RMSE": 7.272258331212408, "R2": 0.6368016898131145, "Memory in Mb": 0.0447597503662109, "Time in s": 0.40948 }, { "step": 198, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 5.229713804713803, "RMSE": 7.766788141562423, "R2": 0.6704650236153215, "Memory in Mb": 0.0442829132080078, "Time in s": 0.46388 }, { "step": 209, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 5.61188197767145, "RMSE": 8.429860803311705, "R2": 0.6799768871245477, "Memory in Mb": 0.0443363189697265, "Time in s": 0.521779 }, { "step": 220, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 6.048560606060604, "RMSE": 9.536044923225656, "R2": 0.6414638231876792, "Memory in Mb": 0.0443096160888671, "Time in s": 0.583178 }, { "step": 231, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 6.582178932178929, "RMSE": 10.20324912411692, "R2": 0.648905367768132, "Memory in Mb": 0.0448932647705078, "Time in s": 0.6480619999999999 }, { "step": 242, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 7.071418732782365, "RMSE": 10.928542055135823, "R2": 0.6759002976153703, "Memory in Mb": 0.0449466705322265, "Time in s": 0.7164429999999999 }, { "step": 253, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 7.477799736495386, "RMSE": 11.323352624926212, "R2": 0.6978095597045382, "Memory in Mb": 0.045053482055664, "Time in s": 0.7883119999999999 }, { "step": 264, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 7.970770202020199, "RMSE": 12.28335187867794, "R2": 0.6750992767833781, "Memory in Mb": 0.0446300506591796, "Time in s": 0.8636689999999999 }, { "step": 275, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 8.55812121212121, "RMSE": 13.382565810664548, "R2": 0.6606476529151027, "Memory in Mb": 0.0446834564208984, "Time in s": 0.942555 }, { "step": 286, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 9.054137529137526, "RMSE": 14.013384412631826, "R2": 0.6777181990167639, "Memory in Mb": 0.0448436737060546, "Time in s": 1.024953 }, { "step": 297, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 9.468967452300786, "RMSE": 14.435360812541292, "R2": 0.7034011013652389, "Memory in Mb": 0.0454006195068359, "Time in s": 1.110877 }, { "step": 308, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 9.90871212121212, "RMSE": 15.173853281638724, "R2": 0.7081243055691319, "Memory in Mb": 0.0454273223876953, "Time in s": 1.200187 }, { "step": 319, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 10.713740856844304, "RMSE": 17.013635837866804, "R2": 0.6670107307192514, "Memory in Mb": 0.0455341339111328, "Time in s": 1.2928449999999998 }, { "step": 330, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 11.460252525252525, "RMSE": 18.125243873896306, "R2": 0.6765805165314649, "Memory in Mb": 0.045083999633789, "Time in s": 1.388826 }, { "step": 341, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 11.901710654936462, "RMSE": 18.5766916053512, "R2": 0.6957870549438744, "Memory in Mb": 0.0451908111572265, "Time in s": 1.488176 }, { "step": 352, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 12.310464015151512, "RMSE": 18.922178666477887, "R2": 0.7130752857476492, "Memory in Mb": 0.0451641082763671, "Time in s": 1.591164 }, { "step": 363, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 12.780394857667584, "RMSE": 19.823234941774256, "R2": 0.694215027528111, "Memory in Mb": 0.0456142425537109, "Time in s": 1.697605 }, { "step": 374, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 13.344073083778964, "RMSE": 20.889730456192645, "R2": 0.6878383009059359, "Memory in Mb": 0.0456142425537109, "Time in s": 1.807438 }, { "step": 385, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 13.830865800865798, "RMSE": 21.557316750546796, "R2": 0.7058815074667231, "Memory in Mb": 0.045694351196289, "Time in s": 1.920665 }, { "step": 396, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 14.08051346801346, "RMSE": 21.615344438143325, "R2": 0.7242879119502419, "Memory in Mb": 0.0452175140380859, "Time in s": 2.037277 }, { "step": 407, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 14.665069615069608, "RMSE": 22.79756192033108, "R2": 0.714918470135155, "Memory in Mb": 0.0452442169189453, "Time in s": 2.157231 }, { "step": 418, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 15.362400318979262, "RMSE": 24.076729101709564, "R2": 0.7015174886253861, "Memory in Mb": 0.0457477569580078, "Time in s": 2.280525 }, { "step": 429, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 15.914413364413358, "RMSE": 24.924104546372128, "R2": 0.7157616535295273, "Memory in Mb": 0.0458278656005859, "Time in s": 2.407192 }, { "step": 440, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 16.21655303030303, "RMSE": 25.17906749713446, "R2": 0.730448642009748, "Memory in Mb": 0.0458545684814453, "Time in s": 2.537243 }, { "step": 451, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 16.571359940872135, "RMSE": 25.529131814454708, "R2": 0.7346810631079229, "Memory in Mb": 0.0458812713623046, "Time in s": 2.670662 }, { "step": 462, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 17.517063492063492, "RMSE": 27.45837911410348, "R2": 0.7117049574257082, "Memory in Mb": 0.0453777313232421, "Time in s": 2.807433 }, { "step": 473, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 18.23357998590557, "RMSE": 28.586680380220997, "R2": 0.7240841374900429, "Memory in Mb": 0.0453510284423828, "Time in s": 2.947633 }, { "step": 484, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 18.61876721763086, "RMSE": 29.038858036362505, "R2": 0.7308884346272555, "Memory in Mb": 0.0458812713623046, "Time in s": 3.0911699999999995 }, { "step": 495, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 19.16138047138048, "RMSE": 29.754410032566323, "R2": 0.7342191699916846, "Memory in Mb": 0.0458812713623046, "Time in s": 3.2380789999999995 }, { "step": 506, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 19.69344532279316, "RMSE": 30.658970587616192, "R2": 0.7260154404176653, "Memory in Mb": 0.0458545684814453, "Time in s": 3.388348 }, { "step": 517, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 20.317762733720187, "RMSE": 31.53258587823862, "R2": 0.7265009007981393, "Memory in Mb": 0.0453777313232421, "Time in s": 3.541995 }, { "step": 528, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 21.03841540404041, "RMSE": 32.63466371480821, "R2": 0.7366125677104822, "Memory in Mb": 0.0454311370849609, "Time in s": 3.699025 }, { "step": 539, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 21.282900432900444, "RMSE": 32.8391739011002, "R2": 0.7443140702924032, "Memory in Mb": 0.0454044342041015, "Time in s": 3.859333 }, { "step": 550, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 21.858333333333334, "RMSE": 33.61129662942374, "R2": 0.7404041745313898, "Memory in Mb": 0.0460147857666015, "Time in s": 4.022901 }, { "step": 561, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 22.36307189542484, "RMSE": 34.18934989679706, "R2": 0.7431446126310046, "Memory in Mb": 0.0460681915283203, "Time in s": 4.189756 }, { "step": 572, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "ChickWeights", "MAE": 22.904341491841496, "RMSE": 34.79445522931405, "R2": 0.7539238777546076, "Memory in Mb": 0.046121597290039, "Time in s": 4.359905 }, { "step": 20, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 2.5579731333333355, "RMSE": 9.79490509533104, "R2": -224.0374880099697, "Memory in Mb": 0.0161190032958984, "Time in s": 0.00492 }, { "step": 40, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 1.814472516666667, "RMSE": 6.975921914401759, "R2": -18.564491994995524, "Memory in Mb": 0.0286769866943359, "Time in s": 0.014556 }, { "step": 60, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 1.386012811111112, "RMSE": 5.70893041508138, "R2": -16.665248891500116, "Memory in Mb": 0.0407314300537109, "Time in s": 0.029158 }, { "step": 80, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 1.1425351583333334, "RMSE": 4.950945892995169, "R2": -12.326934431680348, "Memory in Mb": 0.0527858734130859, "Time in s": 0.04994 }, { "step": 100, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 1.0609460066666667, "RMSE": 4.443635225860514, "R2": -5.735976224554387, "Memory in Mb": 0.065317153930664, "Time in s": 0.078368 }, { "step": 120, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 1.0173975888888886, "RMSE": 4.080152828774464, "R2": -3.8177766328983793, "Memory in Mb": 0.0658702850341796, "Time in s": 0.115087 }, { "step": 140, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.9499007047619044, "RMSE": 3.785073461941064, "R2": -3.284514427728187, "Memory in Mb": 0.0653667449951171, "Time in s": 0.160142 }, { "step": 160, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.8997031916666666, "RMSE": 3.548063392436267, "R2": -2.320037309218333, "Memory in Mb": 0.0653667449951171, "Time in s": 0.213621 }, { "step": 180, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.8894699925925924, "RMSE": 3.3651237174821174, "R2": -1.6229174672077478, "Memory in Mb": 0.0658702850341796, "Time in s": 0.275231 }, { "step": 200, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.8368248133333331, "RMSE": 3.1964619940401167, "R2": -1.3736195901717156, "Memory in Mb": 0.0653667449951171, "Time in s": 0.3451079999999999 }, { "step": 220, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.7973693939393937, "RMSE": 3.051737973437425, "R2": -1.333837761501293, "Memory in Mb": 0.0653667449951171, "Time in s": 0.4231859999999999 }, { "step": 240, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.7882918027777774, "RMSE": 2.9302063484469683, "R2": -1.1678441811700535, "Memory in Mb": 0.0658702850341796, "Time in s": 0.5093219999999999 }, { "step": 260, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.756480287179487, "RMSE": 2.818118800540444, "R2": -1.032185390259123, "Memory in Mb": 0.065500259399414, "Time in s": 0.603278 }, { "step": 280, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.7152656523809521, "RMSE": 2.716213897230066, "R2": -0.9765794643185606, "Memory in Mb": 0.065500259399414, "Time in s": 0.705058 }, { "step": 300, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.6924420288888888, "RMSE": 2.626670145740793, "R2": -0.8178051192110904, "Memory in Mb": 0.0660037994384765, "Time in s": 0.8148869999999999 }, { "step": 320, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.6685162833333335, "RMSE": 2.544831183351663, "R2": -0.7907817018280727, "Memory in Mb": 0.0660037994384765, "Time in s": 0.932496 }, { "step": 340, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.6729953196078432, "RMSE": 2.478015515638401, "R2": -0.7943500832815562, "Memory in Mb": 0.065500259399414, "Time in s": 1.057867 }, { "step": 360, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.6574798574074076, "RMSE": 2.410620514027796, "R2": -0.7120191674014065, "Memory in Mb": 0.0660037994384765, "Time in s": 1.1910109999999998 }, { "step": 380, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.6458375333333335, "RMSE": 2.3511270035956984, "R2": -0.6848943678054311, "Memory in Mb": 0.0660037994384765, "Time in s": 1.3319119999999998 }, { "step": 400, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.6474776666666668, "RMSE": 2.299895164719867, "R2": -0.6578320154352482, "Memory in Mb": 0.065500259399414, "Time in s": 1.4805999999999997 }, { "step": 420, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.6263061492063494, "RMSE": 2.245732257498697, "R2": -0.6329783328857519, "Memory in Mb": 0.0660037994384765, "Time in s": 1.6370479999999996 }, { "step": 440, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.6161101106060607, "RMSE": 2.196509834675512, "R2": -0.5339119919932027, "Memory in Mb": 0.0660037994384765, "Time in s": 1.8010919999999997 }, { "step": 460, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.6114796710144929, "RMSE": 2.151899880839346, "R2": -0.3961217660875815, "Memory in Mb": 0.065500259399414, "Time in s": 1.972734 }, { "step": 480, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.595679659722222, "RMSE": 2.1075134371992843, "R2": -0.3083133320099125, "Memory in Mb": 0.065500259399414, "Time in s": 2.151984 }, { "step": 500, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5871453373333329, "RMSE": 2.067421382434369, "R2": -0.2325961934637197, "Memory in Mb": 0.0660037994384765, "Time in s": 2.338834 }, { "step": 520, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5787837589743586, "RMSE": 2.029002666882104, "R2": -0.1892840306210153, "Memory in Mb": 0.065500259399414, "Time in s": 2.533354 }, { "step": 540, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5648130308641971, "RMSE": 1.991660903442925, "R2": -0.1417123847500625, "Memory in Mb": 0.065500259399414, "Time in s": 2.735472 }, { "step": 560, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5728799083333329, "RMSE": 1.964965242398572, "R2": -0.1377909554693113, "Memory in Mb": 0.0660037994384765, "Time in s": 2.945174 }, { "step": 580, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5729694735632179, "RMSE": 1.9355227317321977, "R2": -0.1312531571152491, "Memory in Mb": 0.065500259399414, "Time in s": 3.162675 }, { "step": 600, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5633090777777773, "RMSE": 1.904172510525728, "R2": -0.0827915396879483, "Memory in Mb": 0.065500259399414, "Time in s": 3.387869 }, { "step": 620, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5627685010752685, "RMSE": 1.877938378401011, "R2": -0.0371083516253996, "Memory in Mb": 0.0660037994384765, "Time in s": 3.620659 }, { "step": 640, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5527265229166664, "RMSE": 1.8490211996046173, "R2": 0.0133784354988776, "Memory in Mb": 0.0660037994384765, "Time in s": 3.861011 }, { "step": 660, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5494711494949491, "RMSE": 1.8235613734746328, "R2": 0.0472618750543785, "Memory in Mb": 0.065500259399414, "Time in s": 4.108899 }, { "step": 680, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5450294392156858, "RMSE": 1.7983422134533726, "R2": 0.05878940572589, "Memory in Mb": 0.0660037994384765, "Time in s": 4.364357 }, { "step": 700, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5469558666666661, "RMSE": 1.7765896178823126, "R2": 0.0572950833274868, "Memory in Mb": 0.0660037994384765, "Time in s": 4.627459 }, { "step": 720, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.543456514814814, "RMSE": 1.7539567687409483, "R2": 0.0609744119033208, "Memory in Mb": 0.065500259399414, "Time in s": 4.898124 }, { "step": 740, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5378193549549544, "RMSE": 1.7312282531924004, "R2": 0.085703628915721, "Memory in Mb": 0.0660037994384765, "Time in s": 5.1763650000000005 }, { "step": 760, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5339037666666662, "RMSE": 1.709797998783685, "R2": 0.0985374850173486, "Memory in Mb": 0.0660037994384765, "Time in s": 5.462206 }, { "step": 780, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5278528008547004, "RMSE": 1.688590710651063, "R2": 0.116822375782677, "Memory in Mb": 0.065500259399414, "Time in s": 5.755616 }, { "step": 800, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5283612208333329, "RMSE": 1.6702821330140922, "R2": 0.1280551636806639, "Memory in Mb": 0.065500259399414, "Time in s": 6.056664 }, { "step": 820, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5218793715447149, "RMSE": 1.650734458460968, "R2": 0.1389919937119252, "Memory in Mb": 0.0660037994384765, "Time in s": 6.365303 }, { "step": 840, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5164909984126979, "RMSE": 1.6320321449108954, "R2": 0.1505777025063954, "Memory in Mb": 0.065500259399414, "Time in s": 6.681529 }, { "step": 860, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5203083496124026, "RMSE": 1.617111920842916, "R2": 0.167474405637749, "Memory in Mb": 0.065500259399414, "Time in s": 7.005502 }, { "step": 880, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5169651212121207, "RMSE": 1.6004898524254525, "R2": 0.188553388101048, "Memory in Mb": 0.0660037994384765, "Time in s": 7.337010999999999 }, { "step": 900, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5126542296296291, "RMSE": 1.583708561642625, "R2": 0.2021320849395992, "Memory in Mb": 0.065500259399414, "Time in s": 7.676102999999999 }, { "step": 920, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5104052702898545, "RMSE": 1.5679886127118026, "R2": 0.2050422348676139, "Memory in Mb": 0.065500259399414, "Time in s": 8.022855999999999 }, { "step": 940, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5051605113475173, "RMSE": 1.551953998854848, "R2": 0.2146112384044058, "Memory in Mb": 0.0660037994384765, "Time in s": 8.377156 }, { "step": 960, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.5025567965277773, "RMSE": 1.5374441378201589, "R2": 0.2211695274632112, "Memory in Mb": 0.0660037994384765, "Time in s": 8.739002999999999 }, { "step": 980, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.4982526563945573, "RMSE": 1.522650494486571, "R2": 0.2212491734260424, "Memory in Mb": 0.065500259399414, "Time in s": 9.108430999999998 }, { "step": 1000, "track": "Regression", "model": "k-Nearest Neighbors", "dataset": "TrumpApproval", "MAE": 0.4939745494666663, "RMSE": 1.5080707141004983, "R2": 0.2232321406133778, "Memory in Mb": 0.0660037994384765, "Time in s": 9.485458999999995 }, { "step": 11, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 8.042756132756132, "RMSE": 17.336048579080593, "R2": -385.8634917094176, "Memory in Mb": 0.0165748596191406, "Time in s": 0.003293 }, { "step": 22, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 4.456785613727984, "RMSE": 12.282422261556867, "R2": -158.770726389092, "Memory in Mb": 0.0181541442871093, "Time in s": 0.009578 }, { "step": 33, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 3.4353973358733074, "RMSE": 10.07037651743448, "R2": -69.4325218162971, "Memory in Mb": 0.0234184265136718, "Time in s": 0.01815 }, { "step": 44, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 2.736909422894262, "RMSE": 8.732393473100391, "R2": -59.03623058514604, "Memory in Mb": 0.0244712829589843, "Time in s": 0.029162 }, { "step": 55, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 2.788577579622257, "RMSE": 8.074088551816661, "R2": -11.726025456653014, "Memory in Mb": 0.0313148498535156, "Time in s": 0.042723 }, { "step": 66, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 3.395880085598137, "RMSE": 7.878422021930021, "R2": -4.223121571879303, "Memory in Mb": 0.0407905578613281, "Time in s": 0.0593589999999999 }, { "step": 77, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 3.889526501621088, "RMSE": 7.800910386370324, "R2": -2.432180745921895, "Memory in Mb": 0.0471076965332031, "Time in s": 0.0796159999999999 }, { "step": 88, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 4.072650698433535, "RMSE": 7.572197783925699, "R2": -1.9320509270116557, "Memory in Mb": 0.0528984069824218, "Time in s": 0.103875 }, { "step": 99, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 4.410984939713907, "RMSE": 7.55185413515251, "R2": -1.439151418709002, "Memory in Mb": 0.0539512634277343, "Time in s": 0.132276 }, { "step": 110, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 4.441558524813062, "RMSE": 7.364764038532391, "R2": -0.6199522309877294, "Memory in Mb": 0.0555305480957031, "Time in s": 0.164898 }, { "step": 121, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 4.487290951327676, "RMSE": 7.260940155844585, "R2": -0.2126939871368238, "Memory in Mb": 0.0555305480957031, "Time in s": 0.201538 }, { "step": 132, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 4.401729970486312, "RMSE": 7.0591187066650845, "R2": 0.0632010249038049, "Memory in Mb": 0.0555305480957031, "Time in s": 0.242248 }, { "step": 143, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 4.303599977233167, "RMSE": 6.863829202938119, "R2": 0.2826256992169514, "Memory in Mb": 0.0560569763183593, "Time in s": 0.2871789999999999 }, { "step": 154, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 4.247967976141752, "RMSE": 6.717580819449276, "R2": 0.4160344373982124, "Memory in Mb": 0.0560569763183593, "Time in s": 0.3361619999999999 }, { "step": 165, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 4.525268599337025, "RMSE": 6.978492074792776, "R2": 0.493394283015475, "Memory in Mb": 0.0560569763183593, "Time in s": 0.3890969999999999 }, { "step": 176, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 4.7434869323510185, "RMSE": 7.161143757518859, "R2": 0.5698598432460567, "Memory in Mb": 0.0565834045410156, "Time in s": 0.4460369999999999 }, { "step": 187, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 4.817684977356876, "RMSE": 7.1877471099050325, "R2": 0.6451941261958376, "Memory in Mb": 0.0565834045410156, "Time in s": 0.5072089999999999 }, { "step": 198, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 4.83667165494537, "RMSE": 7.176577259975889, "R2": 0.7186458480933114, "Memory in Mb": 0.0565834045410156, "Time in s": 0.5725709999999999 }, { "step": 209, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 5.073405719834179, "RMSE": 7.569308518085582, "R2": 0.7419802486075263, "Memory in Mb": 0.0217466354370117, "Time in s": 0.645323 }, { "step": 220, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 5.671396913729996, "RMSE": 8.67042326781336, "R2": 0.7036008152378226, "Memory in Mb": 0.0280637741088867, "Time in s": 0.719465 }, { "step": 231, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 5.870013976865108, "RMSE": 8.892004937785565, "R2": 0.7333469233470653, "Memory in Mb": 0.0333280563354492, "Time in s": 0.7950900000000001 }, { "step": 242, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 6.098410134572789, "RMSE": 9.27860472778795, "R2": 0.7663748869623117, "Memory in Mb": 0.0380659103393554, "Time in s": 0.8723510000000001 }, { "step": 253, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 6.1962339865774, "RMSE": 9.406595007903094, "R2": 0.7914570321252903, "Memory in Mb": 0.0417509078979492, "Time in s": 0.951359 }, { "step": 264, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 6.851942913488504, "RMSE": 10.678395276366356, "R2": 0.7544562538164442, "Memory in Mb": 0.0418310165405273, "Time in s": 1.031981 }, { "step": 275, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 7.351838545672251, "RMSE": 11.801369148896674, "R2": 0.7361015298851068, "Memory in Mb": 0.0418310165405273, "Time in s": 1.114342 }, { "step": 286, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 7.621792166351879, "RMSE": 12.282711040561283, "R2": 0.7524071035845484, "Memory in Mb": 0.0423574447631835, "Time in s": 1.198422 }, { "step": 297, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 7.637256630205925, "RMSE": 12.295347873811286, "R2": 0.7848229800793282, "Memory in Mb": 0.0423574447631835, "Time in s": 1.284253 }, { "step": 308, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 8.1943326666584, "RMSE": 13.18128308543095, "R2": 0.7797471460356308, "Memory in Mb": 0.0423574447631835, "Time in s": 1.3717719999999998 }, { "step": 319, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 9.301321372784988, "RMSE": 15.883856969554804, "R2": 0.7097662534619076, "Memory in Mb": 0.0423574447631835, "Time in s": 1.4609289999999997 }, { "step": 330, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 9.759535973032726, "RMSE": 16.540475274696632, "R2": 0.7306639846914664, "Memory in Mb": 0.0423574447631835, "Time in s": 1.5518979999999998 }, { "step": 341, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 9.98108531256273, "RMSE": 16.6656027575944, "R2": 0.7551596457293974, "Memory in Mb": 0.0423574447631835, "Time in s": 1.6445489999999998 }, { "step": 352, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 10.172493780682656, "RMSE": 16.824682995393008, "R2": 0.773160093080841, "Memory in Mb": 0.0423574447631835, "Time in s": 1.7389499999999998 }, { "step": 363, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 11.068151856114426, "RMSE": 18.263714825485387, "R2": 0.7404354867888504, "Memory in Mb": 0.0423574447631835, "Time in s": 1.835003 }, { "step": 374, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 11.603116520774073, "RMSE": 19.443156920913136, "R2": 0.7295745843003554, "Memory in Mb": 0.0423574447631835, "Time in s": 1.932986 }, { "step": 385, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 12.00507936887919, "RMSE": 20.0961554988217, "R2": 0.744401153020958, "Memory in Mb": 0.0423574447631835, "Time in s": 2.032719 }, { "step": 396, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 12.159003512064782, "RMSE": 20.104597547074984, "R2": 0.7614813985176707, "Memory in Mb": 0.0423574447631835, "Time in s": 2.134109 }, { "step": 407, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 13.058561054914293, "RMSE": 21.64678300128301, "R2": 0.7429728504217219, "Memory in Mb": 0.0393133163452148, "Time in s": 2.2395339999999995 }, { "step": 418, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 13.849374886718222, "RMSE": 23.13707582414104, "R2": 0.7243608784812086, "Memory in Mb": 0.039839744567871, "Time in s": 2.346639 }, { "step": 429, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 14.418764158229274, "RMSE": 24.09396728520024, "R2": 0.7343803671174814, "Memory in Mb": 0.0408926010131835, "Time in s": 2.455353 }, { "step": 440, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 14.611969435637262, "RMSE": 24.1872515908579, "R2": 0.7512659254336986, "Memory in Mb": 0.0414190292358398, "Time in s": 2.5657939999999995 }, { "step": 451, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 15.14954210400284, "RMSE": 24.823452151261105, "R2": 0.7491462990276416, "Memory in Mb": 0.0429983139038085, "Time in s": 2.6778409999999995 }, { "step": 462, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 16.266748325298664, "RMSE": 26.99226997645693, "R2": 0.7214095667925529, "Memory in Mb": 0.0435247421264648, "Time in s": 2.791571 }, { "step": 473, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 17.063164501315207, "RMSE": 28.33702908143248, "R2": 0.7288823142196059, "Memory in Mb": 0.0435247421264648, "Time in s": 2.9070249999999995 }, { "step": 484, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 17.41028324926407, "RMSE": 28.63458736095403, "R2": 0.7383292654808864, "Memory in Mb": 0.0435247421264648, "Time in s": 3.0241479999999994 }, { "step": 495, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 17.881702409973563, "RMSE": 29.18189849457619, "R2": 0.7443486730566713, "Memory in Mb": 0.0435247421264648, "Time in s": 3.1430089999999997 }, { "step": 506, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 18.783373559654446, "RMSE": 30.65392766804094, "R2": 0.7261055653266129, "Memory in Mb": 0.0435247421264648, "Time in s": 3.263499999999999 }, { "step": 517, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 19.52135237811833, "RMSE": 31.66784012367412, "R2": 0.7241496029986892, "Memory in Mb": 0.0435247421264648, "Time in s": 3.3857279999999994 }, { "step": 528, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 20.32410387080197, "RMSE": 32.88418602247989, "R2": 0.7325694870351915, "Memory in Mb": 0.0435247421264648, "Time in s": 3.509655999999999 }, { "step": 539, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 20.50845806362208, "RMSE": 32.89095814819447, "R2": 0.7435070498169007, "Memory in Mb": 0.0435247421264648, "Time in s": 3.635277999999999 }, { "step": 550, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 21.507291986413147, "RMSE": 34.52927015042095, "R2": 0.7260306568753008, "Memory in Mb": 0.0435247421264648, "Time in s": 3.762600999999999 }, { "step": 561, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 22.222091157093345, "RMSE": 35.46412346985515, "R2": 0.7236334646353288, "Memory in Mb": 0.0435247421264648, "Time in s": 3.891587999999999 }, { "step": 572, "track": "Regression", "model": "Hoeffding Tree", "dataset": "ChickWeights", "MAE": 23.084218600655667, "RMSE": 36.66377836765904, "R2": 0.7267728639741885, "Memory in Mb": 0.044051170349121, "Time in s": 4.022359999999999 }, { "step": 20, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 4.834704431652337, "RMSE": 13.708514217962266, "R2": -439.7934984576362, "Memory in Mb": 0.0508193969726562, "Time in s": 0.006949 }, { "step": 40, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 3.4692310697037447, "RMSE": 9.813795721313518, "R2": -37.72035957928713, "Memory in Mb": 0.0739822387695312, "Time in s": 0.020525 }, { "step": 60, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 2.530247618203559, "RMSE": 8.024836796214231, "R2": -33.90460110966681, "Memory in Mb": 0.0866165161132812, "Time in s": 0.041034 }, { "step": 80, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 2.1398752670733447, "RMSE": 6.982837000856316, "R2": -25.510487239912003, "Memory in Mb": 0.09661865234375, "Time in s": 0.06908 }, { "step": 100, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 2.2521629689485394, "RMSE": 6.362737158647257, "R2": -12.810573390910957, "Memory in Mb": 0.1060943603515625, "Time in s": 0.105159 }, { "step": 120, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 2.275331183116589, "RMSE": 5.895687482983747, "R2": -9.059182991303912, "Memory in Mb": 0.1103057861328125, "Time in s": 0.149228 }, { "step": 140, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 2.181766409647037, "RMSE": 5.493495699082884, "R2": -8.025069637302263, "Memory in Mb": 0.1124114990234375, "Time in s": 0.201546 }, { "step": 160, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 2.0641207293789914, "RMSE": 5.165105496730293, "R2": -6.03588310696345, "Memory in Mb": 0.1166229248046875, "Time in s": 0.262282 }, { "step": 180, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.9901037542149176, "RMSE": 4.906162642056599, "R2": -4.575276834209563, "Memory in Mb": 0.1187286376953125, "Time in s": 0.331582 }, { "step": 200, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.854788525917255, "RMSE": 4.661016718308231, "R2": -4.0470005140641305, "Memory in Mb": 0.015085220336914, "Time in s": 0.422383 }, { "step": 220, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.777996659033335, "RMSE": 4.4592908674997, "R2": -3.98319384245183, "Memory in Mb": 0.0312490463256835, "Time in s": 0.517121 }, { "step": 240, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.696058551537428, "RMSE": 4.277699003809556, "R2": -3.620107687238352, "Memory in Mb": 0.0370397567749023, "Time in s": 0.616341 }, { "step": 260, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.6130985138696277, "RMSE": 4.114896288193841, "R2": -3.332738894340625, "Memory in Mb": 0.044569969177246, "Time in s": 0.720441 }, { "step": 280, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.5797289220452373, "RMSE": 3.98595914915012, "R2": -3.256494063385272, "Memory in Mb": 0.0575590133666992, "Time in s": 0.829564 }, { "step": 300, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.5530598651848762, "RMSE": 3.87273637004692, "R2": -2.951592153393709, "Memory in Mb": 0.0675611495971679, "Time in s": 0.944355 }, { "step": 320, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.487708679701559, "RMSE": 3.753298690745279, "R2": -2.895390019001044, "Memory in Mb": 0.0754575729370117, "Time in s": 1.064913 }, { "step": 340, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.447577018485449, "RMSE": 3.651821310152781, "R2": -2.8968902417113367, "Memory in Mb": 0.0807218551635742, "Time in s": 1.191641 }, { "step": 360, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.4679964351503354, "RMSE": 3.577735862687295, "R2": -2.771095017816483, "Memory in Mb": 0.0886182785034179, "Time in s": 1.324785 }, { "step": 380, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.433746711521204, "RMSE": 3.490600620499155, "R2": -2.7138197592485107, "Memory in Mb": 0.0938825607299804, "Time in s": 1.4646529999999998 }, { "step": 400, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.394545215153479, "RMSE": 3.4083536810761967, "R2": -2.640941921411436, "Memory in Mb": 0.1012525558471679, "Time in s": 1.611633 }, { "step": 420, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.3582303513295786, "RMSE": 3.3304244373469776, "R2": -2.5913988321456767, "Memory in Mb": 0.1054639816284179, "Time in s": 1.7657539999999998 }, { "step": 440, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.3237600646089562, "RMSE": 3.2576165394889824, "R2": -2.3739144098898306, "Memory in Mb": 0.1112546920776367, "Time in s": 1.927203 }, { "step": 460, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.313374021763953, "RMSE": 3.19664903268704, "R2": -2.080839603370824, "Memory in Mb": 0.1196775436401367, "Time in s": 2.096272 }, { "step": 480, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.2871329178228548, "RMSE": 3.1331240379472574, "R2": -1.891520259695389, "Memory in Mb": 0.1275739669799804, "Time in s": 2.277254 }, { "step": 500, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.257405891185914, "RMSE": 3.073015209583509, "R2": -1.7232796098685204, "Memory in Mb": 0.1323118209838867, "Time in s": 2.471873 }, { "step": 520, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.236691492049667, "RMSE": 3.017934049641527, "R2": -1.6311150670478525, "Memory in Mb": 0.1375761032104492, "Time in s": 2.675336 }, { "step": 540, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.2120036461347103, "RMSE": 2.9640451937301795, "R2": -1.528689807762199, "Memory in Mb": 0.1396818161010742, "Time in s": 2.8858550000000003 }, { "step": 560, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.1973910792850353, "RMSE": 2.9159627023633448, "R2": -1.5056283897938432, "Memory in Mb": 0.1444196701049804, "Time in s": 3.1010690000000003 }, { "step": 580, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.1729976236433703, "RMSE": 2.867868059269123, "R2": -1.4835996265310456, "Memory in Mb": 0.1470518112182617, "Time in s": 3.321073 }, { "step": 600, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.164383909889498, "RMSE": 2.8255860627341494, "R2": -1.384236602114556, "Memory in Mb": 0.1414899826049804, "Time in s": 3.5505340000000003 }, { "step": 620, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.1607847453289375, "RMSE": 2.7880287925830083, "R2": -1.2858933574415188, "Memory in Mb": 0.1441221237182617, "Time in s": 3.784549 }, { "step": 640, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.1488689392891114, "RMSE": 2.748475985188827, "R2": -1.179970998158682, "Memory in Mb": 0.1462278366088867, "Time in s": 4.023051000000001 }, { "step": 660, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.1353328006378431, "RMSE": 2.711500109160092, "R2": -1.1064542348150137, "Memory in Mb": 0.0933332443237304, "Time in s": 4.270219000000001 }, { "step": 680, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.1237673891934872, "RMSE": 2.67586665558629, "R2": -1.083872122585975, "Memory in Mb": 0.1028089523315429, "Time in s": 4.520950000000001 }, { "step": 700, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.1197870211993892, "RMSE": 2.6450513004918434, "R2": -1.0896316212520398, "Memory in Mb": 0.1107053756713867, "Time in s": 4.77542 }, { "step": 720, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.0988128320741315, "RMSE": 2.6090976903580367, "R2": -1.077879402293885, "Memory in Mb": 0.1170225143432617, "Time in s": 5.033773 }, { "step": 740, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.0821696401958585, "RMSE": 2.5758102479785587, "R2": -1.0239793040320149, "Memory in Mb": 0.1207075119018554, "Time in s": 5.296116 }, { "step": 760, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.0646778366488154, "RMSE": 2.542912274197232, "R2": -0.9939800998628658, "Memory in Mb": 0.1238660812377929, "Time in s": 5.562507999999999 }, { "step": 780, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.0458773095514022, "RMSE": 2.5110610332394967, "R2": -0.953051985319172, "Memory in Mb": 0.1301832199096679, "Time in s": 5.833025999999999 }, { "step": 800, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.037522387437363, "RMSE": 2.4829468635274075, "R2": -0.9268335078372076, "Memory in Mb": 0.1405134201049804, "Time in s": 6.107975999999999 }, { "step": 820, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.0344825476074344, "RMSE": 2.459713101244265, "R2": -0.9117084698305152, "Memory in Mb": 0.1468305587768554, "Time in s": 6.387556999999999 }, { "step": 840, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.0265033672562451, "RMSE": 2.433853565150633, "R2": -0.8891007921837151, "Memory in Mb": 0.1505155563354492, "Time in s": 6.671677999999999 }, { "step": 860, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 1.0098876748057108, "RMSE": 2.406249644034785, "R2": -0.8433117943327111, "Memory in Mb": 0.1520948410034179, "Time in s": 6.960477999999999 }, { "step": 880, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 0.9987418826957182, "RMSE": 2.3807044173500915, "R2": -0.795415858642577, "Memory in Mb": 0.1552534103393554, "Time in s": 7.253952999999999 }, { "step": 900, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 0.9899512872354768, "RMSE": 2.356297962435036, "R2": -0.7662040947107138, "Memory in Mb": 0.1573591232299804, "Time in s": 7.552186999999999 }, { "step": 920, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 0.9763510674237786, "RMSE": 2.3315103197053237, "R2": -0.7576521562914318, "Memory in Mb": 0.1254529953002929, "Time in s": 7.860606999999999 }, { "step": 940, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 0.9721072130212216, "RMSE": 2.310027291919755, "R2": -0.7400479483856388, "Memory in Mb": 0.1344251632690429, "Time in s": 8.173459999999999 }, { "step": 960, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 0.9655343485152448, "RMSE": 2.289186508543074, "R2": -0.7266590967915565, "Memory in Mb": 0.1402158737182617, "Time in s": 8.490537999999999 }, { "step": 980, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 0.9583856890611192, "RMSE": 2.2686834337047155, "R2": -0.7288044208040367, "Memory in Mb": 0.1444272994995117, "Time in s": 8.812014999999999 }, { "step": 1000, "track": "Regression", "model": "Hoeffding Tree", "dataset": "TrumpApproval", "MAE": 0.9497447679766952, "RMSE": 2.248146643879841, "R2": -0.7262238291744263, "Memory in Mb": 0.1486387252807617, "Time in s": 9.137959 }, { "step": 11, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 8.051220648038832, "RMSE": 17.336198122120386, "R2": -385.8701660091343, "Memory in Mb": 0.0232887268066406, "Time in s": 0.00403 }, { "step": 22, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 4.498502947359929, "RMSE": 12.28528637536428, "R2": -158.84524831763767, "Memory in Mb": 0.0249290466308593, "Time in s": 0.011609 }, { "step": 33, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 3.4668695042339137, "RMSE": 10.074636808082968, "R2": -69.49212762837747, "Memory in Mb": 0.0301933288574218, "Time in s": 0.022078 }, { "step": 44, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 2.7637805804889557, "RMSE": 8.735764655686483, "R2": -59.08259408516962, "Memory in Mb": 0.0313072204589843, "Time in s": 0.035307 }, { "step": 55, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 2.814517498310432, "RMSE": 8.074396776941786, "R2": -11.726997097138026, "Memory in Mb": 0.0381507873535156, "Time in s": 0.051286 }, { "step": 66, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 3.396900059747575, "RMSE": 7.862006773633152, "R2": -4.201378762014764, "Memory in Mb": 0.0476264953613281, "Time in s": 0.070551 }, { "step": 77, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 3.8844336568547537, "RMSE": 7.782255505653143, "R2": -2.415785129732385, "Memory in Mb": 0.0540046691894531, "Time in s": 0.093692 }, { "step": 88, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 4.068768385552718, "RMSE": 7.555909217267645, "R2": -1.9194502155140076, "Memory in Mb": 0.0597953796386718, "Time in s": 0.121065 }, { "step": 99, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 4.311602452908636, "RMSE": 7.487314706483316, "R2": -1.3976387620786477, "Memory in Mb": 0.0608482360839843, "Time in s": 0.152902 }, { "step": 110, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 4.261918758035323, "RMSE": 7.240982145259267, "R2": -0.5659557565320237, "Memory in Mb": 0.0624275207519531, "Time in s": 0.189312 }, { "step": 121, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 4.32509570871032, "RMSE": 7.149348278127394, "R2": -0.1757051422939808, "Memory in Mb": 0.0624275207519531, "Time in s": 0.229979 }, { "step": 132, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 4.243770455182887, "RMSE": 6.949556168474376, "R2": 0.0920549285716371, "Memory in Mb": 0.0624275207519531, "Time in s": 0.275055 }, { "step": 143, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 4.119311205048765, "RMSE": 6.740083059431663, "R2": 0.3082592266545521, "Memory in Mb": 0.0241641998291015, "Time in s": 0.330922 }, { "step": 154, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 4.094718549433554, "RMSE": 6.618738421062464, "R2": 0.4330929316851147, "Memory in Mb": 0.034926414489746, "Time in s": 0.389383 }, { "step": 165, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 4.353591485820727, "RMSE": 6.858418841195889, "R2": 0.5106778054828556, "Memory in Mb": 0.041365623474121, "Time in s": 0.450937 }, { "step": 176, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 4.494676115333661, "RMSE": 6.99651956882687, "R2": 0.5894091082089881, "Memory in Mb": 0.0471563339233398, "Time in s": 0.515937 }, { "step": 187, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 4.531460188122701, "RMSE": 6.982633238942946, "R2": 0.6651551017011323, "Memory in Mb": 0.052016258239746, "Time in s": 0.584675 }, { "step": 198, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 4.550856564096301, "RMSE": 6.948954565412159, "R2": 0.736210476532317, "Memory in Mb": 0.0546483993530273, "Time in s": 0.6572239999999999 }, { "step": 209, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 4.745146525796211, "RMSE": 7.286245359964537, "R2": 0.7609173164436883, "Memory in Mb": 0.0546483993530273, "Time in s": 0.733675 }, { "step": 220, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 5.330595718754616, "RMSE": 8.515887777891804, "R2": 0.7140722769094752, "Memory in Mb": 0.0552968978881835, "Time in s": 0.814194 }, { "step": 231, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 5.50563091305374, "RMSE": 8.701126762111178, "R2": 0.7446721431039482, "Memory in Mb": 0.0552968978881835, "Time in s": 0.898563 }, { "step": 242, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 5.723610994733609, "RMSE": 9.068119167211083, "R2": 0.7768542529953268, "Memory in Mb": 0.0552968978881835, "Time in s": 0.986859 }, { "step": 253, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 5.834317193911452, "RMSE": 9.203767847944404, "R2": 0.8003533769470821, "Memory in Mb": 0.0552968978881835, "Time in s": 1.07894 }, { "step": 264, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 6.561326226922799, "RMSE": 10.595386608942691, "R2": 0.7582588922727441, "Memory in Mb": 0.0553770065307617, "Time in s": 1.17475 }, { "step": 275, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 7.055343281410319, "RMSE": 11.793355798881397, "R2": 0.7364597921881992, "Memory in Mb": 0.0553770065307617, "Time in s": 1.274735 }, { "step": 286, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 7.331998951413002, "RMSE": 12.245186296589464, "R2": 0.7539176280650666, "Memory in Mb": 0.0539121627807617, "Time in s": 1.383231 }, { "step": 297, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 7.416966166983629, "RMSE": 12.289761227218738, "R2": 0.7850184759487971, "Memory in Mb": 0.0544385910034179, "Time in s": 1.495361 }, { "step": 308, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 7.99448083149163, "RMSE": 13.217085318753208, "R2": 0.7785490451915651, "Memory in Mb": 0.0545606613159179, "Time in s": 1.6112419999999998 }, { "step": 319, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 9.157233410060112, "RMSE": 16.13339057164046, "R2": 0.7005755447430102, "Memory in Mb": 0.0561399459838867, "Time in s": 1.73087 }, { "step": 330, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 9.47509121278654, "RMSE": 16.446724789755304, "R2": 0.7337084949314072, "Memory in Mb": 0.0561399459838867, "Time in s": 1.854306 }, { "step": 341, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 9.757592549477597, "RMSE": 16.701217161288277, "R2": 0.7541120796137563, "Memory in Mb": 0.0561399459838867, "Time in s": 1.981549 }, { "step": 352, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 9.93501095513177, "RMSE": 16.87017564150386, "R2": 0.7719317193583981, "Memory in Mb": 0.0561399459838867, "Time in s": 2.112498 }, { "step": 363, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 10.85670423687554, "RMSE": 18.405576814105093, "R2": 0.7363875320655082, "Memory in Mb": 0.0561399459838867, "Time in s": 2.247206 }, { "step": 374, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 11.59956477803306, "RMSE": 20.214372545093333, "R2": 0.7076961913412723, "Memory in Mb": 0.0658864974975586, "Time in s": 2.386792 }, { "step": 385, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 12.011712885443345, "RMSE": 20.838356414394227, "R2": 0.7251727140820715, "Memory in Mb": 0.0713338851928711, "Time in s": 2.531165 }, { "step": 396, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 12.02179706392092, "RMSE": 20.699504894468426, "R2": 0.7471567277697432, "Memory in Mb": 0.0781774520874023, "Time in s": 2.680539 }, { "step": 407, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 12.867904342374958, "RMSE": 22.04935022682606, "R2": 0.733324041761514, "Memory in Mb": 0.0825719833374023, "Time in s": 2.8351709999999994 }, { "step": 418, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 13.7726214629037, "RMSE": 23.76360253855293, "R2": 0.7092307493255587, "Memory in Mb": 0.0846776962280273, "Time in s": 2.9951159999999994 }, { "step": 429, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 14.320664029675132, "RMSE": 24.67720892632965, "R2": 0.7213650338700139, "Memory in Mb": 0.0656805038452148, "Time in s": 3.164622 }, { "step": 440, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 14.560745017781516, "RMSE": 24.854467305977835, "R2": 0.7373537773889289, "Memory in Mb": 0.0706624984741211, "Time in s": 3.338776 }, { "step": 451, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 15.05271815758178, "RMSE": 25.416929688531035, "R2": 0.7370081245929037, "Memory in Mb": 0.0787420272827148, "Time in s": 3.5178329999999995 }, { "step": 462, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 16.182360709465044, "RMSE": 27.521690548068367, "R2": 0.7103739673524856, "Memory in Mb": 0.0857076644897461, "Time in s": 3.702085 }, { "step": 473, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 17.028395162723214, "RMSE": 29.038217655150596, "R2": 0.7152989103492285, "Memory in Mb": 0.0888662338256836, "Time in s": 3.891670999999999 }, { "step": 484, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 17.39410374569335, "RMSE": 29.368989764604034, "R2": 0.7247347991767862, "Memory in Mb": 0.0889272689819336, "Time in s": 4.084988999999999 }, { "step": 495, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 17.903720470221085, "RMSE": 29.931789274576047, "R2": 0.7310408495158558, "Memory in Mb": 0.0889272689819336, "Time in s": 4.281388999999999 }, { "step": 506, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 18.828904303353827, "RMSE": 31.360943457558232, "R2": 0.7133254165496098, "Memory in Mb": 0.0895147323608398, "Time in s": 4.480870999999999 }, { "step": 517, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 19.65231385288099, "RMSE": 32.53535290181733, "R2": 0.7088292337107098, "Memory in Mb": 0.0743856430053711, "Time in s": 4.686204999999998 }, { "step": 528, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 20.485248099981963, "RMSE": 33.800991401884744, "R2": 0.7174497851371298, "Memory in Mb": 0.0787191390991211, "Time in s": 4.894319999999999 }, { "step": 539, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 20.62693587606907, "RMSE": 33.76714158926765, "R2": 0.7296595823775684, "Memory in Mb": 0.0872030258178711, "Time in s": 5.105511999999998 }, { "step": 550, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 21.61100465238265, "RMSE": 35.363345192969206, "R2": 0.7126350131259431, "Memory in Mb": 0.0935201644897461, "Time in s": 5.319765999999999 }, { "step": 561, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 22.391562087266266, "RMSE": 36.4058649659661, "R2": 0.708760885936744, "Memory in Mb": 0.0934362411499023, "Time in s": 5.537231999999999 }, { "step": 572, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "ChickWeights", "MAE": 23.25574522992599, "RMSE": 37.57896806973795, "R2": 0.7129622004044582, "Memory in Mb": 0.0946111679077148, "Time in s": 5.757816999999998 }, { "step": 20, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 4.828377634536296, "RMSE": 13.70786256219322, "R2": -439.7515918302183, "Memory in Mb": 0.0575942993164062, "Time in s": 0.005178 }, { "step": 40, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 3.453811275213839, "RMSE": 9.811073218407971, "R2": -37.69887927291551, "Memory in Mb": 0.0808181762695312, "Time in s": 0.01451 }, { "step": 60, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 2.5116544078850294, "RMSE": 8.021960641037959, "R2": -33.879585508404254, "Memory in Mb": 0.0934524536132812, "Time in s": 0.027873 }, { "step": 80, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 2.1224425015381523, "RMSE": 6.9797990571526345, "R2": -25.487425023640156, "Memory in Mb": 0.103515625, "Time in s": 0.045557 }, { "step": 100, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 2.246653919301699, "RMSE": 6.363694444016854, "R2": -12.814729355257526, "Memory in Mb": 0.1129913330078125, "Time in s": 0.06794 }, { "step": 120, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 2.270681160376927, "RMSE": 5.896666779393501, "R2": -9.06252500695684, "Memory in Mb": 0.1172027587890625, "Time in s": 0.095003 }, { "step": 140, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 2.1411489845018936, "RMSE": 5.486121567062232, "R2": -8.000856498367144, "Memory in Mb": 0.1193084716796875, "Time in s": 0.126859 }, { "step": 160, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.9595309296437795, "RMSE": 5.145701533389061, "R2": -5.983118424699933, "Memory in Mb": 0.048110008239746, "Time in s": 0.170894 }, { "step": 180, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.8606850760789413, "RMSE": 4.874784956472401, "R2": -4.504190782470528, "Memory in Mb": 0.0645513534545898, "Time in s": 0.218268 }, { "step": 200, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.753768292507887, "RMSE": 4.635064394721464, "R2": -3.990954055000616, "Memory in Mb": 0.0751142501831054, "Time in s": 0.2693379999999999 }, { "step": 220, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.6442100676088158, "RMSE": 4.426753978888705, "R2": -3.910740120483753, "Memory in Mb": 0.0809926986694336, "Time in s": 0.324221 }, { "step": 240, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.5586094458315778, "RMSE": 4.243291414416048, "R2": -3.546083102970604, "Memory in Mb": 0.0831594467163086, "Time in s": 0.383071 }, { "step": 260, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.4757349309283123, "RMSE": 4.079934399827006, "R2": -3.259426129696055, "Memory in Mb": 0.0869779586791992, "Time in s": 0.445946 }, { "step": 280, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.429182741517093, "RMSE": 3.94384178403937, "R2": -3.1670173911200505, "Memory in Mb": 0.0965147018432617, "Time in s": 0.513038 }, { "step": 300, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.395554812880875, "RMSE": 3.827170050036498, "R2": -2.859150937529973, "Memory in Mb": 0.1050596237182617, "Time in s": 0.584571 }, { "step": 320, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.342072644309252, "RMSE": 3.7085248950294263, "R2": -2.8030066952692625, "Memory in Mb": 0.1113767623901367, "Time in s": 0.660678 }, { "step": 340, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.2981450416106572, "RMSE": 3.6023493777501, "R2": -2.7920215666096264, "Memory in Mb": 0.0969266891479492, "Time in s": 0.7468359999999999 }, { "step": 360, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.3017629599133824, "RMSE": 3.52722030011446, "R2": -2.665355451896766, "Memory in Mb": 0.1048231124877929, "Time in s": 0.837109 }, { "step": 380, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.2791887566109008, "RMSE": 3.4421979658375847, "R2": -2.6115379824259644, "Memory in Mb": 0.1101484298706054, "Time in s": 0.931726 }, { "step": 400, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.2309239845123985, "RMSE": 3.35653802988408, "R2": -2.531080237482485, "Memory in Mb": 0.1175184249877929, "Time in s": 1.030965 }, { "step": 420, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.204488166009232, "RMSE": 3.279580566778272, "R2": -2.4825797995498564, "Memory in Mb": 0.1217298507690429, "Time in s": 1.13497 }, { "step": 440, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.1805943216757937, "RMSE": 3.209931042788128, "R2": -2.2758615914195226, "Memory in Mb": 0.1275205612182617, "Time in s": 1.243696 }, { "step": 460, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.1747748413206256, "RMSE": 3.150463961675437, "R2": -1.9924589881120156, "Memory in Mb": 0.1354780197143554, "Time in s": 1.3572460000000002 }, { "step": 480, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.1643181646721343, "RMSE": 3.0907225956471227, "R2": -1.8137863387673288, "Memory in Mb": 0.1433744430541992, "Time in s": 1.47581 }, { "step": 500, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.1467427258000205, "RMSE": 3.033773569773335, "R2": -1.6541724792729693, "Memory in Mb": 0.1362333297729492, "Time in s": 1.6042770000000002 }, { "step": 520, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.1310531754619513, "RMSE": 2.979836071514613, "R2": -1.5651047078316291, "Memory in Mb": 0.1415586471557617, "Time in s": 1.7377410000000002 }, { "step": 540, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.1142715036195536, "RMSE": 2.927551584361061, "R2": -1.466806182052764, "Memory in Mb": 0.1436643600463867, "Time in s": 1.876231 }, { "step": 560, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.1052485405576076, "RMSE": 2.88137538641146, "R2": -1.4465405352520455, "Memory in Mb": 0.1484022140502929, "Time in s": 2.0198690000000004 }, { "step": 580, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.0859142446379713, "RMSE": 2.834429565013283, "R2": -1.4260211929714153, "Memory in Mb": 0.1510343551635742, "Time in s": 2.168629 }, { "step": 600, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.0769717813954385, "RMSE": 2.7922355683541964, "R2": -1.3282862925750138, "Memory in Mb": 0.1547193527221679, "Time in s": 2.322692 }, { "step": 620, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.0766885404316004, "RMSE": 2.756385805344716, "R2": -1.234299900153052, "Memory in Mb": 0.1578779220581054, "Time in s": 2.481953 }, { "step": 640, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.066276571170311, "RMSE": 2.7176435544384367, "R2": -1.1313354614936588, "Memory in Mb": 0.1599836349487304, "Time in s": 2.646434 }, { "step": 660, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.0564634149761172, "RMSE": 2.6824145051502803, "R2": -1.061505763110988, "Memory in Mb": 0.1636686325073242, "Time in s": 2.816279 }, { "step": 680, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.0488950225738152, "RMSE": 2.6482621618516, "R2": -1.0410990478472515, "Memory in Mb": 0.1663007736206054, "Time in s": 2.991546 }, { "step": 700, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.0494335446356584, "RMSE": 2.619695292588707, "R2": -1.0497603683353351, "Memory in Mb": 0.1547193527221679, "Time in s": 3.177748 }, { "step": 720, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.0311572549278785, "RMSE": 2.584165722213007, "R2": -1.038357615399126, "Memory in Mb": 0.1594572067260742, "Time in s": 3.369155 }, { "step": 740, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 1.0166711191684197, "RMSE": 2.551525288520744, "R2": -0.9859947129346353, "Memory in Mb": 0.1632032394409179, "Time in s": 3.565871 }, { "step": 760, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 0.998612246058934, "RMSE": 2.518502326974768, "R2": -0.9558825700512557, "Memory in Mb": 0.1647825241088867, "Time in s": 3.768021 }, { "step": 780, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 0.9842422617410423, "RMSE": 2.4876653972852822, "R2": -0.916828228451222, "Memory in Mb": 0.1695814132690429, "Time in s": 3.975687 }, { "step": 800, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 0.9822601758268574, "RMSE": 2.462050972175237, "R2": -0.8945384291924348, "Memory in Mb": 0.1616849899291992, "Time in s": 4.194112 }, { "step": 820, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 0.9867607749501652, "RMSE": 2.442599600947298, "R2": -0.8851995145588711, "Memory in Mb": 0.1643171310424804, "Time in s": 4.4181 }, { "step": 840, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 0.9793985197413392, "RMSE": 2.417271328475225, "R2": -0.8634469862274994, "Memory in Mb": 0.1680021286010742, "Time in s": 4.647504 }, { "step": 860, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 0.9647458553132984, "RMSE": 2.3903176435066817, "R2": -0.8189831286734526, "Memory in Mb": 0.1701078414916992, "Time in s": 4.882465 }, { "step": 880, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 0.9550000119490066, "RMSE": 2.3652388018081414, "R2": -0.7721647401587992, "Memory in Mb": 0.1727399826049804, "Time in s": 5.123038 }, { "step": 900, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 0.945028697359752, "RMSE": 2.34076619049233, "R2": -0.7429966155689833, "Memory in Mb": 0.1115369796752929, "Time in s": 5.374164 }, { "step": 920, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 0.9340382087332012, "RMSE": 2.316653968016665, "R2": -0.7353240501222194, "Memory in Mb": 0.1163969039916992, "Time in s": 5.629799 }, { "step": 940, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 0.93159447743873, "RMSE": 2.295899595899596, "R2": -0.7188294143518761, "Memory in Mb": 0.1223096847534179, "Time in s": 5.8899680000000005 }, { "step": 960, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 0.9266882702688716, "RMSE": 2.2758824318695603, "R2": -0.7066477496763941, "Memory in Mb": 0.1296796798706054, "Time in s": 6.154803 }, { "step": 980, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 0.9199947893356224, "RMSE": 2.255690063945526, "R2": -0.7090584581073034, "Memory in Mb": 0.1349439620971679, "Time in s": 6.424549 }, { "step": 1000, "track": "Regression", "model": "Hoeffding Adaptive Tree", "dataset": "TrumpApproval", "MAE": 0.910675347240908, "RMSE": 2.2342958873570486, "R2": -0.7050189374098543, "Memory in Mb": 0.1382246017456054, "Time in s": 6.699174 }, { "step": 11, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 41.63636363636363, "RMSE": 41.64569169030137, "R2": -2231.5319148936137, "Memory in Mb": 0.0096149444580078, "Time in s": 0.001833 }, { "step": 22, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 41.31818181818181, "RMSE": 41.32960638133835, "R2": -1808.0547045951903, "Memory in Mb": 0.0126094818115234, "Time in s": 0.00539 }, { "step": 33, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 41.12121212121212, "RMSE": 41.13871582091424, "R2": -1174.393494897962, "Memory in Mb": 0.015787124633789, "Time in s": 0.009921 }, { "step": 44, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 41.159090909090914, "RMSE": 41.17451771534076, "R2": -1333.7620984139928, "Memory in Mb": 0.0188732147216796, "Time in s": 0.015497 }, { "step": 55, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 41.5090909090909, "RMSE": 41.57075020645253, "R2": -336.3506066081568, "Memory in Mb": 0.0218257904052734, "Time in s": 0.022338 }, { "step": 66, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 42.681818181818166, "RMSE": 42.82080349691271, "R2": -153.29834830483878, "Memory in Mb": 0.0246181488037109, "Time in s": 0.030239 }, { "step": 77, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 43.50649350649351, "RMSE": 43.70978671356627, "R2": -106.75487995129542, "Memory in Mb": 0.0275020599365234, "Time in s": 0.039152 }, { "step": 88, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 44.21590909090909, "RMSE": 44.43649707984724, "R2": -99.97346126163, "Memory in Mb": 0.0300197601318359, "Time in s": 0.049123 }, { "step": 99, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 45.05050505050505, "RMSE": 45.309262771858165, "R2": -86.8022342468144, "Memory in Mb": 0.0329036712646484, "Time in s": 0.060256 }, { "step": 110, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 46.16363636363636, "RMSE": 46.52487115902242, "R2": -63.64797006437341, "Memory in Mb": 0.2696781158447265, "Time in s": 0.074892 }, { "step": 121, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 47.21487603305785, "RMSE": 47.67304278378361, "R2": -51.27707184490422, "Memory in Mb": 0.2696781158447265, "Time in s": 0.095588 }, { "step": 132, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 48.29545454545455, "RMSE": 48.843054157105485, "R2": -43.84882422437649, "Memory in Mb": 0.2696781158447265, "Time in s": 0.122121 }, { "step": 143, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 49.44055944055945, "RMSE": 50.100318941519305, "R2": -37.220279564063546, "Memory in Mb": 0.2696781158447265, "Time in s": 0.154488 }, { "step": 154, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 50.532467532467535, "RMSE": 51.29137544271156, "R2": -33.04474826644667, "Memory in Mb": 0.2696781158447265, "Time in s": 0.192654 }, { "step": 165, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 51.690909090909095, "RMSE": 52.61253451297311, "R2": -27.795548438273773, "Memory in Mb": 0.2696781158447265, "Time in s": 0.236647 }, { "step": 176, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 53.00568181818182, "RMSE": 54.11860921749895, "R2": -23.566226925646237, "Memory in Mb": 0.2696781158447265, "Time in s": 0.286373 }, { "step": 187, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 54.41176470588235, "RMSE": 55.733754017636336, "R2": -20.33250305682894, "Memory in Mb": 0.2696781158447265, "Time in s": 0.341821 }, { "step": 198, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 56.02525252525252, "RMSE": 57.635786091488654, "R2": -17.146924852486976, "Memory in Mb": 0.2696781158447265, "Time in s": 0.403009 }, { "step": 209, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 55.16354936929098, "RMSE": 57.0482200725598, "R2": -13.656313160472004, "Memory in Mb": 0.6838865280151367, "Time in s": 0.4890500000000001 }, { "step": 220, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 53.62203856749311, "RMSE": 56.03531795068661, "R2": -11.37998411824978, "Memory in Mb": 0.6869077682495117, "Time in s": 0.5845720000000001 }, { "step": 231, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 52.77279286370195, "RMSE": 55.29408706815337, "R2": -9.311090357596036, "Memory in Mb": 0.6899290084838867, "Time in s": 0.6897040000000001 }, { "step": 242, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 52.49661908339594, "RMSE": 55.0071045368674, "R2": -7.210918602421254, "Memory in Mb": 0.6929502487182617, "Time in s": 0.8041680000000001 }, { "step": 253, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 52.25631812193077, "RMSE": 54.71344660515688, "R2": -6.055353919833875, "Memory in Mb": 0.6947126388549805, "Time in s": 0.92814 }, { "step": 264, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 51.62511478420569, "RMSE": 54.312843786153664, "R2": -5.352168023774992, "Memory in Mb": 0.6947126388549805, "Time in s": 1.061635 }, { "step": 275, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 51.4425344352617, "RMSE": 54.29364548356293, "R2": -4.585603291722447, "Memory in Mb": 0.6947126388549805, "Time in s": 1.204612 }, { "step": 286, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 51.75651621106165, "RMSE": 54.635705044608144, "R2": -3.8989478253777694, "Memory in Mb": 0.6947126388549805, "Time in s": 1.357118 }, { "step": 297, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 52.373839404142416, "RMSE": 55.25476711535166, "R2": -3.3456400671942, "Memory in Mb": 0.6947126388549805, "Time in s": 1.518976 }, { "step": 308, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 52.87239275875638, "RMSE": 55.86677247417265, "R2": -2.9565197175813718, "Memory in Mb": 0.6947126388549805, "Time in s": 1.690095 }, { "step": 319, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 52.69554478958866, "RMSE": 56.2770501442128, "R2": -2.6433309475704183, "Memory in Mb": 0.6947126388549805, "Time in s": 1.870449 }, { "step": 330, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 53.85316804407712, "RMSE": 57.75044402630399, "R2": -2.2832890424968197, "Memory in Mb": 0.6947126388549805, "Time in s": 2.06005 }, { "step": 341, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 54.90678041411178, "RMSE": 59.01114057562677, "R2": -2.0697921090482247, "Memory in Mb": 0.6947126388549805, "Time in s": 2.258925 }, { "step": 352, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 56.00533746556472, "RMSE": 60.30224520856101, "R2": -1.9140207825503284, "Memory in Mb": 0.6947126388549805, "Time in s": 2.467073 }, { "step": 363, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 55.99599298772852, "RMSE": 60.54917173074773, "R2": -1.852879941931207, "Memory in Mb": 0.6947126388549805, "Time in s": 2.684461 }, { "step": 374, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 56.87222492302705, "RMSE": 61.81275171085535, "R2": -1.7331917323651345, "Memory in Mb": 0.6947126388549805, "Time in s": 2.911073 }, { "step": 385, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 58.41786698150333, "RMSE": 63.95254893573906, "R2": -1.588502821427925, "Memory in Mb": 0.6947126388549805, "Time in s": 3.146928 }, { "step": 396, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 59.7033976124885, "RMSE": 65.46926983257002, "R2": -1.5293357430909813, "Memory in Mb": 0.6947126388549805, "Time in s": 3.392032 }, { "step": 407, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 60.057805647389294, "RMSE": 66.17359973042984, "R2": -1.4019380007417157, "Memory in Mb": 1.1097631454467771, "Time in s": 3.672033 }, { "step": 418, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 59.7070864579051, "RMSE": 66.11592086962122, "R2": -1.2507954049688483, "Memory in Mb": 1.1127843856811523, "Time in s": 3.965768 }, { "step": 429, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 60.122823673891816, "RMSE": 66.73609937588846, "R2": -1.0378169857688957, "Memory in Mb": 1.1158056259155271, "Time in s": 4.272702 }, { "step": 440, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 60.39504675635191, "RMSE": 66.96100690444877, "R2": -0.906365593827489, "Memory in Mb": 1.1188268661499023, "Time in s": 4.593074 }, { "step": 451, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 60.27126048587789, "RMSE": 66.93502892662679, "R2": -0.8239085862185902, "Memory in Mb": 1.120589256286621, "Time in s": 4.926735 }, { "step": 462, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 60.340686610373176, "RMSE": 67.43825007380137, "R2": -0.7390015352251049, "Memory in Mb": 1.120589256286621, "Time in s": 5.273856 }, { "step": 473, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 61.40703262301831, "RMSE": 69.11306667757516, "R2": -0.6127592621572406, "Memory in Mb": 1.120589256286621, "Time in s": 5.634397 }, { "step": 484, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 61.95796621360106, "RMSE": 69.71422620021941, "R2": -0.5510154280248158, "Memory in Mb": 1.120589256286621, "Time in s": 6.008344 }, { "step": 495, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 62.59018166487368, "RMSE": 70.55352405729404, "R2": -0.4943708535906215, "Memory in Mb": 1.120589256286621, "Time in s": 6.395653 }, { "step": 506, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 62.49664579133251, "RMSE": 70.88193125644693, "R2": -0.4644752452013045, "Memory in Mb": 1.120589256286621, "Time in s": 6.796304 }, { "step": 517, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 63.25224079915844, "RMSE": 71.92080214464903, "R2": -0.4228062717918979, "Memory in Mb": 1.120589256286621, "Time in s": 7.21023 }, { "step": 528, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 64.80783657170488, "RMSE": 74.3681944005728, "R2": -0.367764222300833, "Memory in Mb": 1.120589256286621, "Time in s": 7.637592 }, { "step": 539, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 65.59959781369417, "RMSE": 75.30113885843834, "R2": -0.3443906138479853, "Memory in Mb": 1.120589256286621, "Time in s": 8.078512 }, { "step": 550, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 65.79684627343133, "RMSE": 76.01328745307667, "R2": -0.3277190973108916, "Memory in Mb": 1.120589256286621, "Time in s": 8.532886 }, { "step": 561, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 66.6512855136148, "RMSE": 77.20436469287773, "R2": -0.3097569166669509, "Memory in Mb": 1.120589256286621, "Time in s": 9.000807 }, { "step": 572, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "ChickWeights", "MAE": 68.11975592628174, "RMSE": 79.56492566870935, "R2": -0.2867456678376987, "Memory in Mb": 1.120589256286621, "Time in s": 9.482145 }, { "step": 20, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 43.8732195, "RMSE": 43.87807788634269, "R2": -4514.954899312423, "Memory in Mb": 0.0199413299560546, "Time in s": 0.002755 }, { "step": 40, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 42.4932955, "RMSE": 42.52255283421693, "R2": -725.9491167623446, "Memory in Mb": 0.0317363739013671, "Time in s": 0.008058 }, { "step": 60, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 42.2167785, "RMSE": 42.2386240157387, "R2": -966.0073736019044, "Memory in Mb": 0.0438976287841796, "Time in s": 0.015549 }, { "step": 80, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 41.975705625, "RMSE": 41.99760868559829, "R2": -957.9655948743646, "Memory in Mb": 0.0562419891357421, "Time in s": 0.025294 }, { "step": 100, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 41.37550450000001, "RMSE": 41.410913785433536, "R2": -583.9966399141301, "Memory in Mb": 0.5381031036376953, "Time in s": 0.041246 }, { "step": 120, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 40.936110000000006, "RMSE": 40.97829382197767, "R2": -484.9611418859003, "Memory in Mb": 0.5386066436767578, "Time in s": 0.070023 }, { "step": 140, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 40.6885472857143, "RMSE": 40.72961738075088, "R2": -495.1050461477588, "Memory in Mb": 0.5391101837158203, "Time in s": 0.110787 }, { "step": 160, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 40.35105437500001, "RMSE": 40.39801158334292, "R2": -429.4078677932073, "Memory in Mb": 0.5393619537353516, "Time in s": 0.163463 }, { "step": 180, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 40.00981655555555, "RMSE": 40.06373388340122, "R2": -370.7794659133543, "Memory in Mb": 0.5396137237548828, "Time in s": 0.227995 }, { "step": 200, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 39.80633095, "RMSE": 39.860362966711, "R2": -368.1089073295326, "Memory in Mb": 0.5077581405639648, "Time in s": 0.320041 }, { "step": 220, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 36.497516001377406, "RMSE": 38.01945344470104, "R2": -361.2329206514933, "Memory in Mb": 1.3602590560913086, "Time in s": 0.441408 }, { "step": 240, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 33.64243104419191, "RMSE": 36.40668421494773, "R2": -333.65237138497804, "Memory in Mb": 1.360762596130371, "Time in s": 0.581306 }, { "step": 260, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 31.222114965034955, "RMSE": 34.98371838354962, "R2": -312.16748668977897, "Memory in Mb": 1.3610143661499023, "Time in s": 0.739627 }, { "step": 280, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 29.18205946861472, "RMSE": 33.71869814960704, "R2": -303.5986275675674, "Memory in Mb": 1.361769676208496, "Time in s": 0.915776 }, { "step": 300, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 27.34275770505051, "RMSE": 32.57805191350732, "R2": -278.63174197976707, "Memory in Mb": 1.3620214462280271, "Time in s": 1.109879 }, { "step": 320, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 25.81388747443183, "RMSE": 31.5521424826706, "R2": -274.2849072221064, "Memory in Mb": 1.3630285263061523, "Time in s": 1.321838 }, { "step": 340, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 24.51835124153299, "RMSE": 30.62414457186519, "R2": -273.0482727941538, "Memory in Mb": 1.3640356063842771, "Time in s": 1.551694 }, { "step": 360, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 23.451930423400693, "RMSE": 29.78792492645533, "R2": -260.4155562259403, "Memory in Mb": 1.3660497665405271, "Time in s": 1.799643 }, { "step": 380, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 22.46844053349284, "RMSE": 29.014219480552867, "R2": -255.5915105297988, "Memory in Mb": 1.3665533065795898, "Time in s": 2.065559 }, { "step": 400, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 21.59490700757577, "RMSE": 28.301677882839343, "R2": -250.0434007116766, "Memory in Mb": 0.510127067565918, "Time in s": 2.355987 }, { "step": 420, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 20.62268781294523, "RMSE": 27.62086591367872, "R2": -246.0239415518119, "Memory in Mb": 1.3623762130737305, "Time in s": 2.674434 }, { "step": 440, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 19.786863931462925, "RMSE": 26.990398924900397, "R2": -230.60756767519212, "Memory in Mb": 1.3643903732299805, "Time in s": 3.010878 }, { "step": 460, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 19.05732899619648, "RMSE": 26.404670160589287, "R2": -209.2038511633616, "Memory in Mb": 1.3666563034057615, "Time in s": 3.365293 }, { "step": 480, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 18.376512097202227, "RMSE": 25.854792215140314, "R2": -195.90337768575387, "Memory in Mb": 1.3701810836791992, "Time in s": 3.737716 }, { "step": 500, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 17.755044410127518, "RMSE": 25.338820973360427, "R2": -184.1550753065148, "Memory in Mb": 1.3716917037963867, "Time in s": 4.128280999999999 }, { "step": 520, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 17.16611419898163, "RMSE": 24.851444862058347, "R2": -177.4118263333629, "Memory in Mb": 1.3737058639526367, "Time in s": 4.537221 }, { "step": 540, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 16.628565596068775, "RMSE": 24.392285078947275, "R2": -170.25012213753183, "Memory in Mb": 1.3747129440307615, "Time in s": 4.964375 }, { "step": 560, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 16.091244232649693, "RMSE": 23.955027361350904, "R2": -168.10096043791202, "Memory in Mb": 1.3752164840698242, "Time in s": 5.410107999999999 }, { "step": 580, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 15.590768135673304, "RMSE": 23.54051091957351, "R2": -166.33817208986073, "Memory in Mb": 1.3764753341674805, "Time in s": 5.874175999999999 }, { "step": 600, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 15.168708628495342, "RMSE": 23.15108754841241, "R2": -159.05714501634571, "Memory in Mb": 0.5124959945678711, "Time in s": 6.365194 }, { "step": 620, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 14.742446374247312, "RMSE": 22.77953961802373, "R2": -151.59887848495535, "Memory in Mb": 3.064208030700684, "Time in s": 6.921285 }, { "step": 640, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 14.319364852585176, "RMSE": 22.42187566882095, "R2": -144.08105420081068, "Memory in Mb": 3.0679845809936523, "Time in s": 7.51197 }, { "step": 660, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 13.916412195872256, "RMSE": 22.080274918425697, "R2": -138.68241285181185, "Memory in Mb": 3.0712575912475586, "Time in s": 8.136981 }, { "step": 680, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 13.515604789075644, "RMSE": 21.753254558457893, "R2": -136.71797028279042, "Memory in Mb": 3.074782371520996, "Time in s": 8.796442 }, { "step": 700, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 13.16391092204058, "RMSE": 21.44141764506316, "R2": -136.3120101768532, "Memory in Mb": 3.0773000717163086, "Time in s": 9.490636 }, { "step": 720, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 12.828283113852926, "RMSE": 21.142484202016185, "R2": -135.44313416922282, "Memory in Mb": 3.078558921813965, "Time in s": 10.219341 }, { "step": 740, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 12.50446646701278, "RMSE": 20.855361315179096, "R2": -131.6825380828392, "Memory in Mb": 3.0800695419311523, "Time in s": 10.982324 }, { "step": 760, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 12.187542748969031, "RMSE": 20.57929219886472, "R2": -129.592708960364, "Memory in Mb": 3.0813283920288086, "Time in s": 11.779656 }, { "step": 780, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 11.899403743710543, "RMSE": 20.31464229706916, "R2": -126.82553676745258, "Memory in Mb": 3.08359432220459, "Time in s": 12.611571 }, { "step": 800, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 11.634366305883283, "RMSE": 20.06137952581079, "R2": -124.7856004590591, "Memory in Mb": 3.084601402282715, "Time in s": 13.493909000000002 }, { "step": 820, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 11.363415331478278, "RMSE": 19.815492221289517, "R2": -123.0687724200615, "Memory in Mb": 3.08560848236084, "Time in s": 14.412321000000002 }, { "step": 840, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 11.106640469158773, "RMSE": 19.57848368678801, "R2": -121.2430978899656, "Memory in Mb": 3.086615562438965, "Time in s": 15.363464000000002 }, { "step": 860, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 10.873909665943762, "RMSE": 19.35022618912736, "R2": -118.20364312373844, "Memory in Mb": 3.087119102478028, "Time in s": 16.347229000000002 }, { "step": 880, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 10.65545006969969, "RMSE": 19.130035299019603, "R2": -114.92727947355436, "Memory in Mb": 3.0873708724975586, "Time in s": 17.36361 }, { "step": 900, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 10.439309697188907, "RMSE": 18.916827199314994, "R2": -112.83532852765144, "Memory in Mb": 3.08762264251709, "Time in s": 18.412326 }, { "step": 920, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 10.21789524284777, "RMSE": 18.710158789526105, "R2": -112.19133803320568, "Memory in Mb": 3.087874412536621, "Time in s": 19.493438 }, { "step": 940, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 10.012578535125469, "RMSE": 18.510293787577226, "R2": -110.72583714230213, "Memory in Mb": 3.077906608581543, "Time in s": 20.736809 }, { "step": 960, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 9.811853150109153, "RMSE": 18.316579311485903, "R2": -109.54344305213982, "Memory in Mb": 3.0804243087768555, "Time in s": 22.013587 }, { "step": 980, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 9.61909067795052, "RMSE": 18.12881604876013, "R2": -109.39183420714345, "Memory in Mb": 3.080927848815918, "Time in s": 23.322572 }, { "step": 1000, "track": "Regression", "model": "Stochastic Gradient Tree", "dataset": "TrumpApproval", "MAE": 9.438738635632271, "RMSE": 17.946847607318464, "R2": -109.00797869183796, "Memory in Mb": 3.082438468933105, "Time in s": 24.663779 }, { "step": 11, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 7.837563210503649, "RMSE": 16.830121687224917, "R2": -363.61289911513376, "Memory in Mb": 0.1506233215332031, "Time in s": 0.018991 }, { "step": 22, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 4.3557641651310055, "RMSE": 11.925612892987612, "R2": -149.62275175212707, "Memory in Mb": 0.1761512756347656, "Time in s": 0.051966 }, { "step": 33, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 3.371112580593177, "RMSE": 9.780386843070694, "R2": -65.43453306461763, "Memory in Mb": 0.2142868041992187, "Time in s": 0.1028409999999999 }, { "step": 44, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 2.695097509519297, "RMSE": 8.482165721989492, "R2": -55.64483692929184, "Memory in Mb": 0.2312774658203125, "Time in s": 0.1714339999999999 }, { "step": 55, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 2.750371500828058, "RMSE": 7.825470627419848, "R2": -10.954370249441634, "Memory in Mb": 0.2869682312011719, "Time in s": 0.2559499999999999 }, { "step": 66, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 2.874973614360605, "RMSE": 7.312672972792191, "R2": -3.4999113348114523, "Memory in Mb": 0.3332901000976562, "Time in s": 0.3603679999999999 }, { "step": 77, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 3.049190601733834, "RMSE": 7.064366487423796, "R2": -1.814660484448317, "Memory in Mb": 0.3119354248046875, "Time in s": 0.4921819999999999 }, { "step": 88, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 2.9760015514160614, "RMSE": 6.690266116634344, "R2": -1.2888345310585096, "Memory in Mb": 0.3463325500488281, "Time in s": 0.6436869999999999 }, { "step": 99, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 3.4458208345296213, "RMSE": 6.801756467406213, "R2": -0.9786716534372656, "Memory in Mb": 0.3914375305175781, "Time in s": 0.8148389999999999 }, { "step": 110, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 3.8036130411377513, "RMSE": 6.901055458118455, "R2": -0.4223797783359673, "Memory in Mb": 0.4219093322753906, "Time in s": 1.008913 }, { "step": 121, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 4.044286594485068, "RMSE": 6.961321070951229, "R2": -0.1146764842737158, "Memory in Mb": 0.4422340393066406, "Time in s": 1.227422 }, { "step": 132, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 4.278051046290026, "RMSE": 6.992189163715883, "R2": 0.0808809347253165, "Memory in Mb": 0.4695549011230469, "Time in s": 1.467051 }, { "step": 143, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 4.514698307868387, "RMSE": 7.09845673012605, "R2": 0.232743181062298, "Memory in Mb": 0.5039863586425781, "Time in s": 1.72858 }, { "step": 154, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 4.711682816733759, "RMSE": 7.225211881769595, "R2": 0.3244420464758215, "Memory in Mb": 0.5465545654296875, "Time in s": 2.00923 }, { "step": 165, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 5.098965674365188, "RMSE": 7.74448667501397, "R2": 0.3760752970367085, "Memory in Mb": 0.5543212890625, "Time in s": 2.317031 }, { "step": 176, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 5.613573109580669, "RMSE": 8.405070008975855, "R2": 0.4074460804745814, "Memory in Mb": 0.5778732299804688, "Time in s": 2.650775 }, { "step": 187, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 6.0300184245211925, "RMSE": 8.816070592615688, "R2": 0.4662285490406689, "Memory in Mb": 0.597381591796875, "Time in s": 3.008386 }, { "step": 198, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 6.135166503700917, "RMSE": 8.873071763991604, "R2": 0.5699028278126741, "Memory in Mb": 0.6156463623046875, "Time in s": 3.389767 }, { "step": 209, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 6.663870316688535, "RMSE": 9.680163486851024, "R2": 0.5780063435312484, "Memory in Mb": 0.6372909545898438, "Time in s": 3.797698 }, { "step": 220, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 7.114976257039628, "RMSE": 10.70304519196575, "R2": 0.548340525531499, "Memory in Mb": 0.6516532897949219, "Time in s": 4.233731 }, { "step": 231, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 7.558935022860611, "RMSE": 11.205896813348822, "R2": 0.5765126454701623, "Memory in Mb": 0.6456108093261719, "Time in s": 4.696369 }, { "step": 242, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 7.8784966144348445, "RMSE": 11.546829616877767, "R2": 0.6381907286214681, "Memory in Mb": 0.6543197631835938, "Time in s": 5.184542 }, { "step": 253, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 8.045465222989945, "RMSE": 11.7730800696534, "R2": 0.6733287963504477, "Memory in Mb": 0.6542396545410156, "Time in s": 5.698149999999999 }, { "step": 264, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 8.55861765945315, "RMSE": 12.698578392308455, "R2": 0.6527621165047097, "Memory in Mb": 0.7007179260253906, "Time in s": 6.239901999999999 }, { "step": 275, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 9.012932654808608, "RMSE": 13.883768164483952, "R2": 0.6347528903285174, "Memory in Mb": 0.7182159423828125, "Time in s": 6.810226999999999 }, { "step": 286, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 9.46045520422096, "RMSE": 14.421722772543973, "R2": 0.6586625054492083, "Memory in Mb": 0.7397651672363281, "Time in s": 7.406784999999999 }, { "step": 297, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 9.467084537445258, "RMSE": 14.393153360282469, "R2": 0.7051330126585751, "Memory in Mb": 0.6962127685546875, "Time in s": 8.032812 }, { "step": 308, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 9.993822911601686, "RMSE": 15.306673373378164, "R2": 0.7029922374440833, "Memory in Mb": 0.712249755859375, "Time in s": 8.684709 }, { "step": 319, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 10.906399564516825, "RMSE": 17.709412566907307, "R2": 0.6392184800849823, "Memory in Mb": 0.7230567932128906, "Time in s": 9.367603 }, { "step": 330, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 11.354718196032138, "RMSE": 18.25739128586918, "R2": 0.6718473555535345, "Memory in Mb": 0.748199462890625, "Time in s": 10.07931 }, { "step": 341, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 11.709200775641314, "RMSE": 18.709755653596343, "R2": 0.691413317744465, "Memory in Mb": 0.7508468627929688, "Time in s": 10.818764 }, { "step": 352, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 12.007404346564588, "RMSE": 19.02446579939404, "R2": 0.7099648583835785, "Memory in Mb": 0.7794418334960938, "Time in s": 11.583692 }, { "step": 363, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 12.612646669962947, "RMSE": 20.078004824306745, "R2": 0.6863045708062432, "Memory in Mb": 0.8219375610351562, "Time in s": 12.374611 }, { "step": 374, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 13.305874945245664, "RMSE": 21.69198202373745, "R2": 0.6634013148524545, "Memory in Mb": 0.8368568420410156, "Time in s": 13.19172 }, { "step": 385, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 13.874152914620147, "RMSE": 22.398641632517744, "R2": 0.6824761966895349, "Memory in Mb": 0.8399162292480469, "Time in s": 14.039444 }, { "step": 396, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 14.02164789427361, "RMSE": 22.45496751107478, "R2": 0.7024524705388633, "Memory in Mb": 0.8451423645019531, "Time in s": 14.916422 }, { "step": 407, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 14.881080524519056, "RMSE": 23.990711305579165, "R2": 0.684297135752792, "Memory in Mb": 0.844085693359375, "Time in s": 15.821424 }, { "step": 418, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 15.672731015633325, "RMSE": 25.84901428202966, "R2": 0.6559576619146927, "Memory in Mb": 0.8621559143066406, "Time in s": 16.75642 }, { "step": 429, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 16.52730145447373, "RMSE": 27.03527355015745, "R2": 0.6655701177301542, "Memory in Mb": 0.8826904296875, "Time in s": 17.718062999999997 }, { "step": 440, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 16.835543678126854, "RMSE": 27.29532071757395, "R2": 0.6832339396752392, "Memory in Mb": 0.8854255676269531, "Time in s": 18.709096 }, { "step": 451, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 17.2847401584601, "RMSE": 27.83347178305896, "R2": 0.6846223453976918, "Memory in Mb": 0.9156723022460938, "Time in s": 19.725565 }, { "step": 462, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 18.263556988874104, "RMSE": 29.983264015814683, "R2": 0.6562480279042127, "Memory in Mb": 0.9476966857910156, "Time in s": 20.769031 }, { "step": 473, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 19.168820167599023, "RMSE": 31.233753579350584, "R2": 0.6706197338145063, "Memory in Mb": 0.9631462097167968, "Time in s": 21.841163 }, { "step": 484, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 19.66691155441429, "RMSE": 31.66292403296529, "R2": 0.6800549958221269, "Memory in Mb": 0.9797592163085938, "Time in s": 22.942597 }, { "step": 495, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 20.1980005296915, "RMSE": 32.326142080110245, "R2": 0.6862897411402615, "Memory in Mb": 1.003559112548828, "Time in s": 24.073219 }, { "step": 506, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 21.038101965066165, "RMSE": 33.861783151779306, "R2": 0.6657814123530009, "Memory in Mb": 1.0402488708496094, "Time in s": 25.232436 }, { "step": 517, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 21.79336863548733, "RMSE": 34.905834748448235, "R2": 0.6648549707242759, "Memory in Mb": 1.059162139892578, "Time in s": 26.421057 }, { "step": 528, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 22.71415913579816, "RMSE": 36.0778798798642, "R2": 0.6781016272298894, "Memory in Mb": 1.080280303955078, "Time in s": 27.640294 }, { "step": 539, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 22.973012146363907, "RMSE": 36.13494365478664, "R2": 0.690416970144236, "Memory in Mb": 1.1105842590332031, "Time in s": 28.88878 }, { "step": 550, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 23.822482702164027, "RMSE": 37.524990725820025, "R2": 0.6764299185798421, "Memory in Mb": 1.15643310546875, "Time in s": 30.16877 }, { "step": 561, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 24.754282528765707, "RMSE": 38.80763200620001, "R2": 0.669066082535116, "Memory in Mb": 1.1719589233398438, "Time in s": 31.481567 }, { "step": 572, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "ChickWeights", "MAE": 25.964764492717645, "RMSE": 40.6034258569803, "R2": 0.6648997528039327, "Memory in Mb": 1.186126708984375, "Time in s": 32.828648 }, { "step": 20, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 4.656631863584941, "RMSE": 13.301513571178564, "R2": -414.0080590272913, "Memory in Mb": 0.20159912109375, "Time in s": 0.060655 }, { "step": 40, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 3.3092233454389866, "RMSE": 9.514642226769206, "R2": -35.395716979334736, "Memory in Mb": 0.2895278930664062, "Time in s": 0.186458 }, { "step": 60, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 2.370245548222252, "RMSE": 7.779742234417967, "R2": -31.80504797847069, "Memory in Mb": 0.3228263854980469, "Time in s": 0.354007 }, { "step": 80, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 2.0011825545667588, "RMSE": 6.767036502792006, "R2": -23.897224712465302, "Memory in Mb": 0.3692893981933594, "Time in s": 0.55542 }, { "step": 100, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 2.056871489932448, "RMSE": 6.139015712379544, "R2": -11.856454989718417, "Memory in Mb": 0.4076881408691406, "Time in s": 0.79515 }, { "step": 120, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 2.003092266983848, "RMSE": 5.651046465030358, "R2": -8.241693395555247, "Memory in Mb": 0.4241790771484375, "Time in s": 1.072178 }, { "step": 140, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.8854667406427696, "RMSE": 5.2532308662388045, "R2": -7.252888139218157, "Memory in Mb": 0.4439773559570312, "Time in s": 1.385482 }, { "step": 160, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.9340845560700957, "RMSE": 4.984838031470717, "R2": -5.553334350331147, "Memory in Mb": 0.4557876586914062, "Time in s": 1.738613 }, { "step": 180, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.9596878280460808, "RMSE": 4.757627458420989, "R2": -4.242801539132487, "Memory in Mb": 0.4726028442382812, "Time in s": 2.128929 }, { "step": 200, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.9000266951648128, "RMSE": 4.53846274922039, "R2": -3.785084131964374, "Memory in Mb": 0.5018348693847656, "Time in s": 2.555084 }, { "step": 220, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.7756062902244436, "RMSE": 4.331882031903988, "R2": -3.702506681895046, "Memory in Mb": 0.5390548706054688, "Time in s": 3.014926 }, { "step": 240, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.722064335127714, "RMSE": 4.161337926832492, "R2": -3.3721758647478204, "Memory in Mb": 0.5583267211914062, "Time in s": 3.510014 }, { "step": 260, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.668741133448935, "RMSE": 4.009095884933904, "R2": -3.112800247055813, "Memory in Mb": 0.5867843627929688, "Time in s": 4.039729 }, { "step": 280, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.596023168515899, "RMSE": 3.86837254754146, "R2": -3.0090634555073343, "Memory in Mb": 0.6034698486328125, "Time in s": 4.6068750000000005 }, { "step": 300, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.5862781822088614, "RMSE": 3.757725401796155, "R2": -2.72037165832895, "Memory in Mb": 0.6344451904296875, "Time in s": 5.213001 }, { "step": 320, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.5269819355711358, "RMSE": 3.644015209511257, "R2": -2.67185104068617, "Memory in Mb": 0.6524238586425781, "Time in s": 5.854158 }, { "step": 340, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.4570659608871932, "RMSE": 3.537119081966105, "R2": -2.6559352799702967, "Memory in Mb": 0.6771697998046875, "Time in s": 6.534176 }, { "step": 360, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.4064005847783465, "RMSE": 3.441784227878547, "R2": -2.4899419787597266, "Memory in Mb": 0.7120590209960938, "Time in s": 7.253771 }, { "step": 380, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.353481677960258, "RMSE": 3.352627624678765, "R2": -2.426029812278527, "Memory in Mb": 0.7612266540527344, "Time in s": 8.012458 }, { "step": 400, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.3254238940946812, "RMSE": 3.27422063813923, "R2": -2.360008106665105, "Memory in Mb": 0.7831077575683594, "Time in s": 8.809453000000001 }, { "step": 420, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.2822507927277378, "RMSE": 3.197239276537114, "R2": -2.309899038967682, "Memory in Mb": 0.8153495788574219, "Time in s": 9.645719 }, { "step": 440, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.2469389910195894, "RMSE": 3.127027882921648, "R2": -2.108834809107039, "Memory in Mb": 0.8549957275390625, "Time in s": 10.520540000000002 }, { "step": 460, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.209007072666545, "RMSE": 3.060196802253249, "R2": -1.8234356170996369, "Memory in Mb": 0.8641319274902344, "Time in s": 11.437965000000002 }, { "step": 480, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.173565091899577, "RMSE": 2.996986036098964, "R2": -1.6456994146583188, "Memory in Mb": 0.9048995971679688, "Time in s": 12.395296000000002 }, { "step": 500, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.1545102154576106, "RMSE": 2.9412312685847275, "R2": -1.494716293761022, "Memory in Mb": 0.9429206848144532, "Time in s": 13.397268000000002 }, { "step": 520, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.1235341152888954, "RMSE": 2.885679937630878, "R2": -1.4055626483775598, "Memory in Mb": 0.9187583923339844, "Time in s": 14.455292000000002 }, { "step": 540, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.0931325909773704, "RMSE": 2.8325152336083046, "R2": -1.3092471918321815, "Memory in Mb": 0.9785118103027344, "Time in s": 15.562633000000002 }, { "step": 560, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.080423433010604, "RMSE": 2.7861157835692825, "R2": -1.2874470666919131, "Memory in Mb": 0.8416099548339844, "Time in s": 16.721025 }, { "step": 580, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.0538460644054608, "RMSE": 2.73873459117484, "R2": -1.2649736085810763, "Memory in Mb": 0.9269638061523438, "Time in s": 17.931443 }, { "step": 600, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.037762850657022, "RMSE": 2.6954140775252133, "R2": -1.1696179031883165, "Memory in Mb": 1.0152244567871094, "Time in s": 19.191903 }, { "step": 620, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.022747434499167, "RMSE": 2.654976815796094, "R2": -1.0729218181826925, "Memory in Mb": 0.968769073486328, "Time in s": 20.501534 }, { "step": 640, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 1.006861222675929, "RMSE": 2.615186194972241, "R2": -0.9736586966592728, "Memory in Mb": 0.803070068359375, "Time in s": 21.860299 }, { "step": 660, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.9869414277387362, "RMSE": 2.5762284524749504, "R2": -0.9015227260176624, "Memory in Mb": 0.7759437561035156, "Time in s": 23.260671 }, { "step": 680, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.966244541930286, "RMSE": 2.538677410892474, "R2": -0.8756731719459285, "Memory in Mb": 0.8428535461425781, "Time in s": 24.702724 }, { "step": 700, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.9583039577617944, "RMSE": 2.5060806369029174, "R2": -0.8758219540617476, "Memory in Mb": 0.9465827941894532, "Time in s": 26.183847 }, { "step": 720, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.9436352676783604, "RMSE": 2.472672874668102, "R2": -0.8662636043278715, "Memory in Mb": 1.0379486083984375, "Time in s": 27.712492 }, { "step": 740, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.9279533445219876, "RMSE": 2.44025252932111, "R2": -0.816552178803118, "Memory in Mb": 1.1120071411132812, "Time in s": 29.286906 }, { "step": 760, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.9160723193407864, "RMSE": 2.4102496967776017, "R2": -0.7913569678512289, "Memory in Mb": 1.17376708984375, "Time in s": 30.91286 }, { "step": 780, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.8969957702252379, "RMSE": 2.379401465215729, "R2": -0.753616871824967, "Memory in Mb": 1.2616004943847656, "Time in s": 32.587144 }, { "step": 800, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.8879951793456313, "RMSE": 2.351379467833174, "R2": -0.7280439441517783, "Memory in Mb": 1.355243682861328, "Time in s": 34.314383 }, { "step": 820, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.8778121160020841, "RMSE": 2.323761508818731, "R2": -0.7062232791684944, "Memory in Mb": 1.4321250915527344, "Time in s": 36.09551 }, { "step": 840, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.8674818777939237, "RMSE": 2.297554956673723, "R2": -0.683441607427212, "Memory in Mb": 1.4874954223632812, "Time in s": 37.948423 }, { "step": 860, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.8596582290799093, "RMSE": 2.2724190258224723, "R2": -0.6439714465644337, "Memory in Mb": 1.5595359802246094, "Time in s": 39.857894 }, { "step": 880, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.8554226716886886, "RMSE": 2.248810009475745, "R2": -0.601989379910626, "Memory in Mb": 1.6191024780273438, "Time in s": 41.823765 }, { "step": 900, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.8440517106498798, "RMSE": 2.2244180426447486, "R2": -0.5740310312005918, "Memory in Mb": 1.1261253356933594, "Time in s": 43.8642 }, { "step": 920, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.8347159483348575, "RMSE": 2.201058546919984, "R2": -0.5664676720057789, "Memory in Mb": 1.1678504943847656, "Time in s": 45.946931000000006 }, { "step": 940, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.8262269751007542, "RMSE": 2.1790511985851078, "R2": -0.5483240613297584, "Memory in Mb": 1.119964599609375, "Time in s": 48.07255500000001 }, { "step": 960, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.8159800926650994, "RMSE": 2.1571455676024542, "R2": -0.5332153251602936, "Memory in Mb": 1.1733894348144531, "Time in s": 50.238479000000005 }, { "step": 980, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.80675324923832, "RMSE": 2.1360469188887925, "R2": -0.5325676025464574, "Memory in Mb": 1.2283477783203125, "Time in s": 52.4464 }, { "step": 1000, "track": "Regression", "model": "Adaptive Random Forest", "dataset": "TrumpApproval", "MAE": 0.801132918984696, "RMSE": 2.116027645482028, "R2": -0.5292923269414216, "Memory in Mb": 1.2836189270019531, "Time in s": 54.694244000000005 }, { "step": 11, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 4.664574314574316, "RMSE": 12.7079745317607, "R2": -206.87879383707747, "Memory in Mb": 0.0196142196655273, "Time in s": 0.002799 }, { "step": 22, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 2.767694704637076, "RMSE": 9.018587183866767, "R2": -85.14025986830408, "Memory in Mb": 0.0211782455444335, "Time in s": 0.009348 }, { "step": 33, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 2.3093367298127023, "RMSE": 7.420500566500976, "R2": -37.24267181629702, "Memory in Mb": 0.0263471603393554, "Time in s": 0.018276 }, { "step": 44, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 1.892363968348808, "RMSE": 6.441521936619904, "R2": -31.668094594906044, "Memory in Mb": 0.0274343490600585, "Time in s": 0.0297909999999999 }, { "step": 55, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 2.1129412159858934, "RMSE": 6.114058653243701, "R2": -6.297346571779499, "Memory in Mb": 0.0340337753295898, "Time in s": 0.044022 }, { "step": 66, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 2.832849782567835, "RMSE": 6.236602142425367, "R2": -2.2730130120415795, "Memory in Mb": 0.043257713317871, "Time in s": 0.061336 }, { "step": 77, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 3.4069290990236856, "RMSE": 6.402381882180361, "R2": -1.3118663438824, "Memory in Mb": 0.0494871139526367, "Time in s": 0.082289 }, { "step": 88, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 3.650377971160808, "RMSE": 6.321189272940957, "R2": -1.043267371916866, "Memory in Mb": 0.0551328659057617, "Time in s": 0.107232 }, { "step": 99, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 4.035631404360372, "RMSE": 6.4483291916176695, "R2": -0.7783857772357967, "Memory in Mb": 0.0562467575073242, "Time in s": 0.136317 }, { "step": 110, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 4.693189868957898, "RMSE": 7.0697740144659305, "R2": -0.4927792786841307, "Memory in Mb": 0.0576238632202148, "Time in s": 0.169599 }, { "step": 121, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 5.274396860168236, "RMSE": 7.6542276724395, "R2": -0.3476225254437259, "Memory in Mb": 0.0577573776245117, "Time in s": 0.206842 }, { "step": 132, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 5.247611065864998, "RMSE": 7.56430675955835, "R2": -0.0756815066101803, "Memory in Mb": 0.0578107833862304, "Time in s": 0.2481519999999999 }, { "step": 143, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 5.084413296044263, "RMSE": 7.343803904848652, "R2": 0.1787885014844915, "Memory in Mb": 0.058394432067871, "Time in s": 0.2937619999999999 }, { "step": 154, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 4.973008915037768, "RMSE": 7.173430375731751, "R2": 0.3340904988080935, "Memory in Mb": 0.0584478378295898, "Time in s": 0.343499 }, { "step": 165, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 5.201973475639973, "RMSE": 7.389818367745889, "R2": 0.4319135436678196, "Memory in Mb": 0.0584478378295898, "Time in s": 0.397279 }, { "step": 176, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 5.377897753885034, "RMSE": 7.538080975572278, "R2": 0.5233859928595415, "Memory in Mb": 0.0590581893920898, "Time in s": 0.455134 }, { "step": 187, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 5.414777515271245, "RMSE": 7.541781669769663, "R2": 0.6093812059493195, "Memory in Mb": 0.0591115951538085, "Time in s": 0.517245 }, { "step": 198, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 5.40059238519783, "RMSE": 7.511878220104288, "R2": 0.6917410630009373, "Memory in Mb": 0.0590581893920898, "Time in s": 0.583523 }, { "step": 209, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 5.933708937482518, "RMSE": 9.717098931216649, "R2": 0.5747798982216288, "Memory in Mb": 0.0252752304077148, "Time in s": 0.662886 }, { "step": 220, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 6.498767742677896, "RMSE": 10.515698120348512, "R2": 0.5640139167754625, "Memory in Mb": 0.0314245223999023, "Time in s": 0.744596 }, { "step": 231, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 6.70504504336628, "RMSE": 10.67374680573752, "R2": 0.6157790851383267, "Memory in Mb": 0.0365400314331054, "Time in s": 0.828906 }, { "step": 242, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 7.118759598962231, "RMSE": 11.248237924166032, "R2": 0.6566609789141779, "Memory in Mb": 0.0410718917846679, "Time in s": 0.916125 }, { "step": 253, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 7.339750662382254, "RMSE": 11.39871112384624, "R2": 0.6937739359440155, "Memory in Mb": 0.0445966720581054, "Time in s": 1.006337 }, { "step": 264, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 7.866457552558359, "RMSE": 12.301057885719082, "R2": 0.6741619364384577, "Memory in Mb": 0.0447034835815429, "Time in s": 1.099545 }, { "step": 275, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 8.421243223038738, "RMSE": 13.285884557144795, "R2": 0.6655331879845522, "Memory in Mb": 0.0447034835815429, "Time in s": 1.19574 }, { "step": 286, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 8.956033363560122, "RMSE": 14.109625220244896, "R2": 0.6732762786849746, "Memory in Mb": 0.0452070236206054, "Time in s": 1.295357 }, { "step": 297, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 9.573413802719209, "RMSE": 14.887232530340055, "R2": 0.6845415314559343, "Memory in Mb": 0.0452337265014648, "Time in s": 1.398184 }, { "step": 308, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 10.140823162094344, "RMSE": 15.798657858475249, "R2": 0.6835926538539661, "Memory in Mb": 0.0452604293823242, "Time in s": 1.504001 }, { "step": 319, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 11.05646041165176, "RMSE": 17.826108509419473, "R2": 0.6344480842540857, "Memory in Mb": 0.0452604293823242, "Time in s": 1.6128270000000002 }, { "step": 330, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 11.706749123156325, "RMSE": 18.647901518188576, "R2": 0.6576594092850414, "Memory in Mb": 0.0452871322631835, "Time in s": 1.7247210000000002 }, { "step": 341, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 11.849547188265053, "RMSE": 18.683751607733637, "R2": 0.6922705096711406, "Memory in Mb": 0.0452871322631835, "Time in s": 1.839831 }, { "step": 352, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 11.96088648820193, "RMSE": 18.74329807265456, "R2": 0.7184745225672177, "Memory in Mb": 0.0452871322631835, "Time in s": 1.958081 }, { "step": 363, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 12.783089048199372, "RMSE": 19.95838853158221, "R2": 0.6900311672733117, "Memory in Mb": 0.0453138351440429, "Time in s": 2.0793790000000003 }, { "step": 374, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 13.27307991721093, "RMSE": 20.988857849066505, "R2": 0.6848686892374445, "Memory in Mb": 0.0453405380249023, "Time in s": 2.203704 }, { "step": 385, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 13.623649100869688, "RMSE": 21.545378780740656, "R2": 0.7062071700264252, "Memory in Mb": 0.0453405380249023, "Time in s": 2.331151 }, { "step": 396, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 13.714864044781413, "RMSE": 21.4916185882578, "R2": 0.7274352207736796, "Memory in Mb": 0.0453405380249023, "Time in s": 2.4617500000000003 }, { "step": 407, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 14.57407318940339, "RMSE": 22.90334645043852, "R2": 0.712266679293069, "Memory in Mb": 0.0456800460815429, "Time in s": 2.5991990000000005 }, { "step": 418, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 15.311297276648313, "RMSE": 24.25392212062312, "R2": 0.6971079497894322, "Memory in Mb": 0.0457334518432617, "Time in s": 2.7396560000000005 }, { "step": 429, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 15.833945440380871, "RMSE": 25.12811892959106, "R2": 0.7110893860103431, "Memory in Mb": 0.0457334518432617, "Time in s": 2.8832220000000004 }, { "step": 440, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 15.995632485589844, "RMSE": 25.20571130808328, "R2": 0.7298778762133054, "Memory in Mb": 0.0456533432006835, "Time in s": 3.0299210000000003 }, { "step": 451, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 16.482571154231422, "RMSE": 25.77399383544894, "R2": 0.7295670550023294, "Memory in Mb": 0.0461835861206054, "Time in s": 3.179584 }, { "step": 462, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 17.556958821758087, "RMSE": 27.82207110996992, "R2": 0.7040173234911381, "Memory in Mb": 0.0469274520874023, "Time in s": 3.3322830000000003 }, { "step": 473, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 18.31809908164516, "RMSE": 29.103026344234387, "R2": 0.7140266770057507, "Memory in Mb": 0.046980857849121, "Time in s": 3.488055 }, { "step": 484, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 18.645508344467764, "RMSE": 29.39095020592674, "R2": 0.7243229903014706, "Memory in Mb": 0.0469541549682617, "Time in s": 3.646969 }, { "step": 495, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 19.076944683969508, "RMSE": 29.900823849283483, "R2": 0.7315970559213162, "Memory in Mb": 0.0469007492065429, "Time in s": 3.808963 }, { "step": 506, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 19.9412049113122, "RMSE": 31.299098765867257, "R2": 0.7144549629170223, "Memory in Mb": 0.046980857849121, "Time in s": 3.97409 }, { "step": 517, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 20.652539482762663, "RMSE": 32.28122969713156, "R2": 0.7133599532452177, "Memory in Mb": 0.0470075607299804, "Time in s": 4.142383000000001 }, { "step": 528, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 21.437431132207102, "RMSE": 33.471760575953454, "R2": 0.7229272102715563, "Memory in Mb": 0.0470075607299804, "Time in s": 4.313758000000001 }, { "step": 539, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 21.589008276225865, "RMSE": 33.459905509370415, "R2": 0.7345566785536845, "Memory in Mb": 0.0470075607299804, "Time in s": 4.488246000000001 }, { "step": 550, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 22.551700866868885, "RMSE": 35.03737693702089, "R2": 0.717908278090669, "Memory in Mb": 0.0470342636108398, "Time in s": 4.665796000000001 }, { "step": 561, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 23.243872726229487, "RMSE": 35.949191367533466, "R2": 0.7160216409608307, "Memory in Mb": 0.0470075607299804, "Time in s": 4.846464000000001 }, { "step": 572, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "ChickWeights", "MAE": 24.092513885911806, "RMSE": 37.13693189688246, "R2": 0.7196752558485364, "Memory in Mb": 0.0469541549682617, "Time in s": 5.030284000000001 }, { "step": 20, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 2.695184981652336, "RMSE": 9.807184976514188, "R2": -224.6021011118197, "Memory in Mb": 0.0538091659545898, "Time in s": 0.005953 }, { "step": 40, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 2.3994713447037435, "RMSE": 7.102066178895935, "R2": -19.27845129783118, "Memory in Mb": 0.0761518478393554, "Time in s": 0.016156 }, { "step": 60, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.8170744682035584, "RMSE": 5.815253847056423, "R2": -17.329373299766118, "Memory in Mb": 0.0883970260620117, "Time in s": 0.0302489999999999 }, { "step": 80, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.604995404573344, "RMSE": 5.081770494168446, "R2": -13.040545957103586, "Memory in Mb": 0.0980443954467773, "Time in s": 0.0484799999999999 }, { "step": 100, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.824259078948539, "RMSE": 4.70488333223354, "R2": -6.5512954222403845, "Memory in Mb": 0.1071348190307617, "Time in s": 0.071134 }, { "step": 120, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.918744608116588, "RMSE": 4.412336880489357, "R2": -4.634185300646759, "Memory in Mb": 0.1113233566284179, "Time in s": 0.098322 }, { "step": 140, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.8761207739327503, "RMSE": 4.13187920011476, "R2": -4.105616799680584, "Memory in Mb": 0.1133375167846679, "Time in s": 0.13009 }, { "step": 160, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.961232939518506, "RMSE": 3.976173487274506, "R2": -3.1695661963674864, "Memory in Mb": 0.1174459457397461, "Time in s": 0.166507 }, { "step": 180, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 2.066134597500757, "RMSE": 3.873731518767916, "R2": -2.4756944369169624, "Memory in Mb": 0.1194601058959961, "Time in s": 0.207686 }, { "step": 200, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 2.051125997923389, "RMSE": 3.731810291394655, "R2": -2.23527456693896, "Memory in Mb": 0.0176219940185546, "Time in s": 0.262943 }, { "step": 220, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 2.0738811328897206, "RMSE": 4.417664564856108, "R2": -3.890594467356201, "Memory in Mb": 0.0358037948608398, "Time in s": 0.32065 }, { "step": 240, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.9726100065438288, "RMSE": 4.237524240975239, "R2": -3.5337340888030546, "Memory in Mb": 0.0415029525756835, "Time in s": 0.38109 }, { "step": 260, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.8594315384151243, "RMSE": 4.074751007989252, "R2": -3.248610147038553, "Memory in Mb": 0.0488462448120117, "Time in s": 0.444412 }, { "step": 280, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.7773205119132678, "RMSE": 3.936654153117972, "R2": -3.1518424972300867, "Memory in Mb": 0.0637922286987304, "Time in s": 0.510957 }, { "step": 300, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.8265705896173516, "RMSE": 3.8591002097544127, "R2": -2.923813511442849, "Memory in Mb": 0.0735006332397461, "Time in s": 0.581026 }, { "step": 320, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.7437620649419607, "RMSE": 3.7394874649640353, "R2": -2.8667745903740336, "Memory in Mb": 0.0810804367065429, "Time in s": 0.6546050000000001 }, { "step": 340, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.7029951846067328, "RMSE": 3.640753753244776, "R2": -2.873305462857122, "Memory in Mb": 0.0861959457397461, "Time in s": 0.7321480000000001 }, { "step": 360, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.691125588823449, "RMSE": 3.557868621003357, "R2": -2.729329365262769, "Memory in Mb": 0.0937833786010742, "Time in s": 0.8137190000000001 }, { "step": 380, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.641476039217788, "RMSE": 3.4678199943963026, "R2": -2.665503107324644, "Memory in Mb": 0.0988988876342773, "Time in s": 0.8994270000000001 }, { "step": 400, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.6260112424669562, "RMSE": 3.3952504336469187, "R2": -2.613000890937967, "Memory in Mb": 0.1061162948608398, "Time in s": 0.989373 }, { "step": 420, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.6289201270983786, "RMSE": 3.3343146523246907, "R2": -2.599793842225358, "Memory in Mb": 0.1101179122924804, "Time in s": 1.08339 }, { "step": 440, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.667060123646852, "RMSE": 3.302206999442347, "R2": -2.466911261860751, "Memory in Mb": 0.1157636642456054, "Time in s": 1.1816330000000002 }, { "step": 460, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.69667104754334, "RMSE": 3.2720484626443, "R2": -2.2278892819413008, "Memory in Mb": 0.1238470077514648, "Time in s": 1.2846220000000002 }, { "step": 480, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.6506098779434175, "RMSE": 3.2067821053781245, "R2": -2.029074572324324, "Memory in Mb": 0.1315069198608398, "Time in s": 1.3924660000000002 }, { "step": 500, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.6365240614669594, "RMSE": 3.1603547309397078, "R2": -1.8802784791951508, "Memory in Mb": 0.0784368515014648, "Time in s": 1.505205 }, { "step": 520, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.6536721067944389, "RMSE": 3.126560253923372, "R2": -1.823930193625598, "Memory in Mb": 0.0835790634155273, "Time in s": 1.621512 }, { "step": 540, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.6698160029512246, "RMSE": 3.0946441969309766, "R2": -1.7564325082786318, "Memory in Mb": 0.0873861312866211, "Time in s": 1.745676 }, { "step": 560, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.6408841434358417, "RMSE": 3.046586581366264, "R2": -1.735141389893172, "Memory in Mb": 0.0885534286499023, "Time in s": 1.8735 }, { "step": 580, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.6127327645791831, "RMSE": 2.999611374258061, "R2": -1.7170225021123482, "Memory in Mb": 0.0890569686889648, "Time in s": 2.004994 }, { "step": 600, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.6269498006919805, "RMSE": 2.973082395326553, "R2": -1.6396488808638732, "Memory in Mb": 0.0909147262573242, "Time in s": 2.140229 }, { "step": 620, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.64112955570108, "RMSE": 2.949075530135499, "R2": -1.5576036781852802, "Memory in Mb": 0.0923452377319336, "Time in s": 2.27922 }, { "step": 640, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.6562657927450175, "RMSE": 2.9273758724267736, "R2": -1.4729982020585646, "Memory in Mb": 0.0944395065307617, "Time in s": 2.422009 }, { "step": 660, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.6610090165740414, "RMSE": 2.900076441293188, "R2": -1.409637238697782, "Memory in Mb": 0.0960302352905273, "Time in s": 2.568661 }, { "step": 680, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.640070345532056, "RMSE": 2.8623424740678667, "R2": -1.3844340745604549, "Memory in Mb": 0.0981245040893554, "Time in s": 2.7190639999999995 }, { "step": 700, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.6119603204138224, "RMSE": 2.8240252200668348, "R2": -1.381983091116742, "Memory in Mb": 0.1015691757202148, "Time in s": 2.8733429999999998 }, { "step": 720, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.589173412563986, "RMSE": 2.788316481605285, "R2": -1.3731423466582644, "Memory in Mb": 0.1027364730834961, "Time in s": 3.031541 }, { "step": 740, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.5872474989945902, "RMSE": 2.762320631839069, "R2": -1.3276973292362433, "Memory in Mb": 0.1038503646850586, "Time in s": 3.198810999999999 }, { "step": 760, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.573860293324891, "RMSE": 2.731605449949154, "R2": -1.3008801881813965, "Memory in Mb": 0.1038503646850586, "Time in s": 3.3700799999999997 }, { "step": 780, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.5672492734296428, "RMSE": 2.7047187411026274, "R2": -1.2659143323804294, "Memory in Mb": 0.1064214706420898, "Time in s": 3.5453349999999992 }, { "step": 800, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.5527653312522924, "RMSE": 2.676901954415756, "R2": -1.2396196471003753, "Memory in Mb": 0.1070318222045898, "Time in s": 3.7247 }, { "step": 820, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.5366430278321572, "RMSE": 2.648967131435787, "R2": -1.2172052322327516, "Memory in Mb": 0.1085958480834961, "Time in s": 3.908095 }, { "step": 840, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.5234128351461855, "RMSE": 2.622526466573217, "R2": -1.1933402061449063, "Memory in Mb": 0.1101598739624023, "Time in s": 4.095543999999999 }, { "step": 860, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.520997799745444, "RMSE": 2.601206078568585, "R2": -1.1541054380753062, "Memory in Mb": 0.1107702255249023, "Time in s": 4.287108999999999 }, { "step": 880, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.4988763963538276, "RMSE": 2.573388458013685, "R2": -1.0978034673380694, "Memory in Mb": 0.1112470626831054, "Time in s": 4.482816999999999 }, { "step": 900, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.4758663089418147, "RMSE": 2.54594713286987, "R2": -1.061955243276925, "Memory in Mb": 0.1116437911987304, "Time in s": 4.682644999999999 }, { "step": 920, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.462937696730923, "RMSE": 2.523979038782575, "R2": -1.059822201667401, "Memory in Mb": 0.1116704940795898, "Time in s": 4.886850999999999 }, { "step": 940, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.4561394845136584, "RMSE": 2.50519739840106, "R2": -1.0464959899330828, "Memory in Mb": 0.1127042770385742, "Time in s": 5.100838999999999 }, { "step": 960, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.4393535919618172, "RMSE": 2.483254475687026, "R2": -1.0318268701719249, "Memory in Mb": 0.1132078170776367, "Time in s": 5.318975999999998 }, { "step": 980, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.4209594300543067, "RMSE": 2.4596960058574417, "R2": -1.0321742156649796, "Memory in Mb": 0.1138181686401367, "Time in s": 5.541285999999999 }, { "step": 1000, "track": "Regression", "model": "Adaptive Model Rules", "dataset": "TrumpApproval", "MAE": 1.4020445673510784, "RMSE": 2.4364355463770164, "R2": -1.027485181852556, "Memory in Mb": 0.1144285202026367, "Time in s": 5.767785999999998 }, { "step": 11, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 4.674710287324511, "RMSE": 12.709622005759083, "R2": -206.93269654300337, "Memory in Mb": 0.1438665390014648, "Time in s": 0.043578 }, { "step": 22, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 2.741934273684416, "RMSE": 9.017856101646904, "R2": -85.12629469646626, "Memory in Mb": 0.1680784225463867, "Time in s": 0.114891 }, { "step": 33, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 2.321314094852809, "RMSE": 7.424021720293775, "R2": -37.27897402435965, "Memory in Mb": 0.2096052169799804, "Time in s": 0.217395 }, { "step": 44, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 1.9425031371298072, "RMSE": 6.446443185481759, "R2": -31.71802976156788, "Memory in Mb": 0.2417478561401367, "Time in s": 0.352059 }, { "step": 55, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 2.220127898780405, "RMSE": 6.120501061993398, "R2": -6.312733162160137, "Memory in Mb": 0.3060827255249023, "Time in s": 0.516621 }, { "step": 66, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 2.329752126186388, "RMSE": 5.733717860182345, "R2": -1.7664593315707076, "Memory in Mb": 0.3567266464233398, "Time in s": 0.719974 }, { "step": 77, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 2.702798931003846, "RMSE": 5.8295610878248265, "R2": -0.9166874006339528, "Memory in Mb": 0.3732900619506836, "Time in s": 0.96062 }, { "step": 88, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 2.6099619817757915, "RMSE": 5.526618942218035, "R2": -0.5618763668879856, "Memory in Mb": 0.4128637313842773, "Time in s": 1.239929 }, { "step": 99, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 2.746820956366501, "RMSE": 5.433915350818854, "R2": -0.2628661224764999, "Memory in Mb": 0.4623746871948242, "Time in s": 1.563224 }, { "step": 110, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 2.8880448046427323, "RMSE": 5.393209741308231, "R2": 0.131281330475993, "Memory in Mb": 0.5318593978881836, "Time in s": 1.933351 }, { "step": 121, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 3.102793618966865, "RMSE": 5.4667968998241765, "R2": 0.312565398150165, "Memory in Mb": 0.5604543685913086, "Time in s": 2.356966 }, { "step": 132, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 3.301393875206229, "RMSE": 5.777687225912497, "R2": 0.3724425463943938, "Memory in Mb": 0.1946859359741211, "Time in s": 2.834547 }, { "step": 143, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 3.2818761969220303, "RMSE": 5.651296511520541, "R2": 0.5136946280960023, "Memory in Mb": 0.2288389205932617, "Time in s": 3.343438 }, { "step": 154, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 3.2515588511167266, "RMSE": 5.538190901897615, "R2": 0.6030852117170243, "Memory in Mb": 0.2577199935913086, "Time in s": 3.884102 }, { "step": 165, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 3.5490619378471253, "RMSE": 5.901472315915889, "R2": 0.6377005660204649, "Memory in Mb": 0.2627325057983398, "Time in s": 4.460716 }, { "step": 176, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 3.748099204740288, "RMSE": 6.114989482363781, "R2": 0.6863562530103127, "Memory in Mb": 0.2941198348999023, "Time in s": 5.073099 }, { "step": 187, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 3.855321751115436, "RMSE": 6.172883744230479, "R2": 0.7383134393857906, "Memory in Mb": 0.3320951461791992, "Time in s": 5.716163 }, { "step": 198, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 4.064611732985858, "RMSE": 6.634154210053631, "R2": 0.7595694090278171, "Memory in Mb": 0.2527418136596679, "Time in s": 6.400463 }, { "step": 209, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 4.2854283677061895, "RMSE": 7.034301545827039, "R2": 0.7771654635449772, "Memory in Mb": 0.3202161788940429, "Time in s": 7.116785 }, { "step": 220, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 4.87812017832838, "RMSE": 8.464168223538273, "R2": 0.7175347810295998, "Memory in Mb": 0.3510808944702148, "Time in s": 7.873189 }, { "step": 231, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 5.139510271881338, "RMSE": 8.709209118107985, "R2": 0.7441975817879227, "Memory in Mb": 0.3200139999389648, "Time in s": 8.671972 }, { "step": 242, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 5.512568989147682, "RMSE": 9.214318878962654, "R2": 0.7696009669773758, "Memory in Mb": 0.3710927963256836, "Time in s": 9.508629 }, { "step": 253, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 5.61462831814645, "RMSE": 9.300369065456374, "R2": 0.7961404678287027, "Memory in Mb": 0.4192609786987304, "Time in s": 10.381303 }, { "step": 264, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 6.307820522062941, "RMSE": 10.632794713133398, "R2": 0.7565488951511344, "Memory in Mb": 0.3416013717651367, "Time in s": 11.288641 }, { "step": 275, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 6.788015101176612, "RMSE": 11.834244259749068, "R2": 0.7346291964126817, "Memory in Mb": 0.3569021224975586, "Time in s": 12.231102 }, { "step": 286, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 7.083325494446596, "RMSE": 12.279756566760542, "R2": 0.7525262008661281, "Memory in Mb": 0.3965520858764648, "Time in s": 13.20812 }, { "step": 297, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 7.191320030958258, "RMSE": 12.343414248948324, "R2": 0.7831373025283351, "Memory in Mb": 0.4258260726928711, "Time in s": 14.218151 }, { "step": 308, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 7.797209174725968, "RMSE": 13.278742843330225, "R2": 0.7764780945249113, "Memory in Mb": 0.4501142501831054, "Time in s": 15.260696 }, { "step": 319, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 8.817827198046418, "RMSE": 15.9696940597815, "R2": 0.7066209046531168, "Memory in Mb": 0.4718656539916992, "Time in s": 16.339578 }, { "step": 330, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 9.357743221083844, "RMSE": 16.830542617885925, "R2": 0.7211345584533546, "Memory in Mb": 0.3236379623413086, "Time in s": 17.459623999999998 }, { "step": 341, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 9.597227793355117, "RMSE": 16.978620563243194, "R2": 0.7458759585671038, "Memory in Mb": 0.3676939010620117, "Time in s": 18.612921 }, { "step": 352, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 9.7373515968392, "RMSE": 17.046818432657442, "R2": 0.7671306392320572, "Memory in Mb": 0.3629522323608398, "Time in s": 19.795535999999995 }, { "step": 363, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 10.474784553852622, "RMSE": 18.420082712462506, "R2": 0.7359718490826586, "Memory in Mb": 0.3571195602416992, "Time in s": 21.012742 }, { "step": 374, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 11.136965297216438, "RMSE": 20.001694167276444, "R2": 0.7138145773791849, "Memory in Mb": 0.3998785018920898, "Time in s": 22.263945 }, { "step": 385, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 11.663755213802826, "RMSE": 20.72310945995512, "R2": 0.7282041838356077, "Memory in Mb": 0.3288450241088867, "Time in s": 23.553922 }, { "step": 396, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 11.794892571100942, "RMSE": 20.71536814309967, "R2": 0.7467690419180344, "Memory in Mb": 0.4024953842163086, "Time in s": 24.874665 }, { "step": 407, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 12.7361976076631, "RMSE": 22.396840643020628, "R2": 0.7248523596518419, "Memory in Mb": 0.4475545883178711, "Time in s": 26.248019 }, { "step": 418, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 13.669165628181592, "RMSE": 24.17119440887557, "R2": 0.6991706950778176, "Memory in Mb": 0.4968290328979492, "Time in s": 27.657996 }, { "step": 429, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 14.21091951782044, "RMSE": 24.907688885339496, "R2": 0.7161359437094021, "Memory in Mb": 0.5376424789428711, "Time in s": 29.100111 }, { "step": 440, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 14.453337266265764, "RMSE": 25.002813963201465, "R2": 0.7342091543116155, "Memory in Mb": 0.5657072067260742, "Time in s": 30.577019 }, { "step": 451, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 14.795462221424788, "RMSE": 25.396591749368834, "R2": 0.7374288341656263, "Memory in Mb": 0.2583265304565429, "Time in s": 32.092868 }, { "step": 462, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 16.121556592117344, "RMSE": 28.147488646444906, "R2": 0.6970529793362255, "Memory in Mb": 0.3047628402709961, "Time in s": 33.634783000000006 }, { "step": 473, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 16.919755395139642, "RMSE": 29.31210430009691, "R2": 0.7099030173412568, "Memory in Mb": 0.3544912338256836, "Time in s": 35.20760200000001 }, { "step": 484, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 17.222944705236912, "RMSE": 29.519121223412064, "R2": 0.7219133474565596, "Memory in Mb": 0.3983259201049804, "Time in s": 36.808400000000006 }, { "step": 495, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 17.875632407347712, "RMSE": 30.34841895302658, "R2": 0.7235012910446976, "Memory in Mb": 0.4324254989624023, "Time in s": 38.43633400000001 }, { "step": 506, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 18.888217233083253, "RMSE": 31.835585198521954, "R2": 0.7045822227904736, "Memory in Mb": 0.4678411483764648, "Time in s": 40.09290200000001 }, { "step": 517, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 19.824673890348247, "RMSE": 33.232962754926376, "R2": 0.6962090391160322, "Memory in Mb": 0.4975500106811523, "Time in s": 41.78457100000001 }, { "step": 528, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 20.55396214529221, "RMSE": 34.09704280994323, "R2": 0.712478586733055, "Memory in Mb": 0.5351285934448242, "Time in s": 43.50851800000001 }, { "step": 539, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 20.794926737672743, "RMSE": 34.209729391662115, "R2": 0.7225264054992676, "Memory in Mb": 0.576685905456543, "Time in s": 45.26814300000001 }, { "step": 550, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 21.840113545070352, "RMSE": 36.13121679398973, "R2": 0.7000199686285788, "Memory in Mb": 0.4753904342651367, "Time in s": 47.07007900000001 }, { "step": 561, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 22.59682566601873, "RMSE": 37.08324430393829, "R2": 0.6978222813826447, "Memory in Mb": 0.5189352035522461, "Time in s": 48.90757000000001 }, { "step": 572, "track": "Regression", "model": "Streaming Random Patches", "dataset": "ChickWeights", "MAE": 23.516206925607506, "RMSE": 38.207190389030345, "R2": 0.703284935102584, "Memory in Mb": 0.5585355758666992, "Time in s": 50.782863000000006 }, { "step": 20, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 2.677140920600926, "RMSE": 9.804891856735376, "R2": -224.4966127051096, "Memory in Mb": 0.2373647689819336, "Time in s": 0.10297 }, { "step": 40, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 2.227777813220112, "RMSE": 7.083306817310631, "R2": -19.171465983096805, "Memory in Mb": 0.3270711898803711, "Time in s": 0.289755 }, { "step": 60, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 1.615301860635012, "RMSE": 5.7908261762165685, "R2": -17.175707266102673, "Memory in Mb": 0.3493108749389648, "Time in s": 0.561259 }, { "step": 80, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 1.3541232617236425, "RMSE": 5.026566774725167, "R2": -12.73715546617699, "Memory in Mb": 0.3968191146850586, "Time in s": 0.918423 }, { "step": 100, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 1.2177336486572592, "RMSE": 4.516233376106315, "R2": -5.957872973758095, "Memory in Mb": 0.4107885360717773, "Time in s": 1.362708 }, { "step": 120, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 1.1154353306650455, "RMSE": 4.135716354504269, "R2": -3.949887064372274, "Memory in Mb": 0.4562673568725586, "Time in s": 1.881933 }, { "step": 140, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 1.2694693870086102, "RMSE": 4.857381406328817, "R2": -6.05598089151511, "Memory in Mb": 0.2026891708374023, "Time in s": 2.479905 }, { "step": 160, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 1.197729670480587, "RMSE": 4.553187715474859, "R2": -4.467532002416268, "Memory in Mb": 0.3215742111206054, "Time in s": 3.138645 }, { "step": 180, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 1.1382354235034091, "RMSE": 4.302111654125532, "R2": -3.2869252353070264, "Memory in Mb": 0.4017667770385742, "Time in s": 3.869636 }, { "step": 200, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 1.0619299314905082, "RMSE": 4.083716699099621, "R2": -2.874210730330613, "Memory in Mb": 0.4772901535034179, "Time in s": 4.674132999999999 }, { "step": 220, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 1.009898171671029, "RMSE": 3.898715068147509, "R2": -2.8090719143731837, "Memory in Mb": 0.5200605392456055, "Time in s": 5.552957999999999 }, { "step": 240, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.9646445055554522, "RMSE": 3.736185930434801, "R2": -2.5244277699140394, "Memory in Mb": 0.590418815612793, "Time in s": 6.501358999999999 }, { "step": 260, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.9172332240820484, "RMSE": 3.59133014967386, "R2": -2.300314999970906, "Memory in Mb": 0.677699089050293, "Time in s": 7.522147999999999 }, { "step": 280, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.8713372213927624, "RMSE": 3.461793231901636, "R2": -2.2106176891844487, "Memory in Mb": 0.7459287643432617, "Time in s": 8.615362 }, { "step": 300, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.8589405406556339, "RMSE": 3.350216865329824, "R2": -1.9572094631572516, "Memory in Mb": 0.8300580978393555, "Time in s": 9.791068 }, { "step": 320, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.8332253596869799, "RMSE": 3.2462964384589745, "R2": -1.91407713381932, "Memory in Mb": 0.8134641647338867, "Time in s": 11.051061 }, { "step": 340, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.8452804825423809, "RMSE": 3.1781241500612394, "R2": -1.9514868559348704, "Memory in Mb": 0.7938528060913086, "Time in s": 12.398121 }, { "step": 360, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.8633895166787324, "RMSE": 3.1040171399305283, "R2": -1.8385669899509445, "Memory in Mb": 0.8660383224487305, "Time in s": 13.839894 }, { "step": 380, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.8513159306308952, "RMSE": 3.0258511220091995, "R2": -1.790715802132521, "Memory in Mb": 0.930495262145996, "Time in s": 15.372487 }, { "step": 400, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.8510161564157176, "RMSE": 2.9641796059686003, "R2": -1.7538068241726803, "Memory in Mb": 0.9046812057495116, "Time in s": 17.004842 }, { "step": 420, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.8518447067444684, "RMSE": 2.91289276041272, "R2": -1.747346648183163, "Memory in Mb": 0.2984609603881836, "Time in s": 18.737382 }, { "step": 440, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.8395925714721912, "RMSE": 2.8496340177457244, "R2": -1.5817388594042834, "Memory in Mb": 0.3453207015991211, "Time in s": 20.534513 }, { "step": 460, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.8276812048623222, "RMSE": 2.790693875069675, "R2": -1.3480296319058032, "Memory in Mb": 0.3807516098022461, "Time in s": 22.405168 }, { "step": 480, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.8089244758990292, "RMSE": 2.7333778802045163, "R2": -1.2007484949677454, "Memory in Mb": 0.4482488632202148, "Time in s": 24.346508 }, { "step": 500, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.7928829832001318, "RMSE": 2.679994202833863, "R2": -1.0712404739849797, "Memory in Mb": 0.4975194931030273, "Time in s": 26.364916 }, { "step": 520, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.7968627360462042, "RMSE": 2.655906961990266, "R2": -1.037727311679443, "Memory in Mb": 0.3753881454467773, "Time in s": 28.465481 }, { "step": 540, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.7742648164612971, "RMSE": 2.606576025481956, "R2": -0.9555400217068246, "Memory in Mb": 0.4063673019409179, "Time in s": 30.635854 }, { "step": 560, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.7686196547282114, "RMSE": 2.5632583130611786, "R2": -0.9361432250468024, "Memory in Mb": 0.4374494552612304, "Time in s": 32.873421 }, { "step": 580, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.7604339230100455, "RMSE": 2.522208925126442, "R2": -0.9209911676265596, "Memory in Mb": 0.4967718124389648, "Time in s": 35.174013 }, { "step": 600, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.7505205215384793, "RMSE": 2.4816305596178174, "R2": -0.839105014250833, "Memory in Mb": 0.569575309753418, "Time in s": 37.541938 }, { "step": 620, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.7415649894603582, "RMSE": 2.4434454055931187, "R2": -0.7557664113175795, "Memory in Mb": 0.6584272384643555, "Time in s": 39.976025 }, { "step": 640, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.7318408439896782, "RMSE": 2.406886195682516, "R2": -0.6717754169622376, "Memory in Mb": 0.7120962142944336, "Time in s": 42.479937 }, { "step": 660, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.7165688958291918, "RMSE": 2.37061113672817, "R2": -0.6101020988109156, "Memory in Mb": 0.8089780807495117, "Time in s": 45.058017 }, { "step": 680, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.7019759043195819, "RMSE": 2.336022363731008, "R2": -0.5881668313132071, "Memory in Mb": 0.8398160934448242, "Time in s": 47.720249 }, { "step": 700, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.7046161229979929, "RMSE": 2.307765546298159, "R2": -0.5906876272832315, "Memory in Mb": 0.9275884628295898, "Time in s": 50.471651 }, { "step": 720, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.699791115281057, "RMSE": 2.2802792890719745, "R2": -0.5871418479715558, "Memory in Mb": 0.9087285995483398, "Time in s": 53.310919 }, { "step": 740, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.6993154625867034, "RMSE": 2.2532668970074776, "R2": -0.5488294820654547, "Memory in Mb": 0.8719320297241211, "Time in s": 56.236366 }, { "step": 760, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.6904813287783395, "RMSE": 2.224703478329614, "R2": -0.5261679577762028, "Memory in Mb": 0.929518699645996, "Time in s": 59.248631 }, { "step": 780, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.6809571474431378, "RMSE": 2.1968956754751456, "R2": -0.4949206250779803, "Memory in Mb": 1.0446271896362305, "Time in s": 62.34821899999999 }, { "step": 800, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.6801944660295238, "RMSE": 2.1726014141558028, "R2": -0.4752630155166446, "Memory in Mb": 1.1031560897827148, "Time in s": 65.54039399999999 }, { "step": 820, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.6800251543540311, "RMSE": 2.1538267014914845, "R2": -0.4657984869085023, "Memory in Mb": 1.0328702926635742, "Time in s": 68.82165799999999 }, { "step": 840, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.6756860923792902, "RMSE": 2.1342936501586, "R2": -0.4526954783446735, "Memory in Mb": 0.7475957870483398, "Time in s": 72.18837399999998 }, { "step": 860, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.6733560632024954, "RMSE": 2.111426905397114, "R2": -0.4192847599850244, "Memory in Mb": 0.8119535446166992, "Time in s": 75.62699399999998 }, { "step": 880, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.6699617254268444, "RMSE": 2.0889651464935617, "R2": -0.3823451381863831, "Memory in Mb": 0.8655576705932617, "Time in s": 79.14156799999998 }, { "step": 900, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.6641763033522209, "RMSE": 2.070781028281848, "R2": -0.3641082228169974, "Memory in Mb": 0.8467855453491211, "Time in s": 82.73512999999998 }, { "step": 920, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.6581948551182502, "RMSE": 2.04921868376074, "R2": -0.3577970506072152, "Memory in Mb": 0.9400205612182616, "Time in s": 86.40810799999998 }, { "step": 940, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.6518145768911946, "RMSE": 2.0285221107553344, "R2": -0.3417959776408932, "Memory in Mb": 0.8168668746948242, "Time in s": 90.15720199999998 }, { "step": 960, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.6459384626205039, "RMSE": 2.0083339154310043, "R2": -0.328972794111009, "Memory in Mb": 0.9120321273803712, "Time in s": 93.98330699999998 }, { "step": 980, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.6434185155449816, "RMSE": 1.989534246313576, "R2": -0.3295384550375804, "Memory in Mb": 0.9782476425170898, "Time in s": 97.888458 }, { "step": 1000, "track": "Regression", "model": "Streaming Random Patches", "dataset": "TrumpApproval", "MAE": 0.6405613133684143, "RMSE": 1.9713432953350207, "R2": -0.3273099653285773, "Memory in Mb": 1.0593442916870115, "Time in s": 101.872577 }, { "step": 11, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 10.961585696594296, "RMSE": 17.742218537059934, "R2": -404.203665453531, "Memory in Mb": 0.1782550811767578, "Time in s": 0.00837 }, { "step": 22, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 5.889263372306967, "RMSE": 12.56756036562654, "R2": -166.2750319368382, "Memory in Mb": 0.1910533905029297, "Time in s": 0.024461 }, { "step": 33, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 4.385855416063054, "RMSE": 10.300574999811516, "R2": -72.68935558725912, "Memory in Mb": 0.2280941009521484, "Time in s": 0.04853 }, { "step": 44, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 3.447994945519213, "RMSE": 8.931729546653537, "R2": -61.80843214992921, "Memory in Mb": 0.2438068389892578, "Time in s": 0.081553 }, { "step": 55, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 3.35253400433443, "RMSE": 8.24824849102831, "R2": -12.280953122644297, "Memory in Mb": 0.2916851043701172, "Time in s": 0.123768 }, { "step": 66, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 3.890626377385135, "RMSE": 8.046318086318358, "R2": -4.448112248710658, "Memory in Mb": 0.3612346649169922, "Time in s": 0.176552 }, { "step": 77, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 4.3386080839549335, "RMSE": 7.968508799771546, "R2": -2.581242138287016, "Memory in Mb": 0.4169635772705078, "Time in s": 0.2426829999999999 }, { "step": 88, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 4.490657725713863, "RMSE": 7.741140850532905, "R2": -2.064344233357061, "Memory in Mb": 0.4634113311767578, "Time in s": 0.322916 }, { "step": 99, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 4.7848487383098295, "RMSE": 7.706963997319479, "R2": -1.5403773740733393, "Memory in Mb": 0.4844684600830078, "Time in s": 0.418203 }, { "step": 110, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 4.819508170706054, "RMSE": 7.525876668153812, "R2": -0.6916040970280823, "Memory in Mb": 0.5139484405517578, "Time in s": 0.528794 }, { "step": 121, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 4.831868630589585, "RMSE": 7.4067264415397105, "R2": -0.261880180240535, "Memory in Mb": 0.5271091461181641, "Time in s": 0.654758 }, { "step": 132, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 4.689813959013141, "RMSE": 7.185628463196342, "R2": 0.0293225226637304, "Memory in Mb": 0.5355319976806641, "Time in s": 0.796727 }, { "step": 143, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 4.575735548989308, "RMSE": 6.988996035323699, "R2": 0.2562234762018912, "Memory in Mb": 0.5445156097412109, "Time in s": 0.954849 }, { "step": 154, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 4.5047654468276, "RMSE": 6.840884466051986, "R2": 0.3943998861813385, "Memory in Mb": 0.5490932464599609, "Time in s": 1.128949 }, { "step": 165, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 4.788922390491115, "RMSE": 7.112527411058041, "R2": 0.4737467226899117, "Memory in Mb": 0.5519008636474609, "Time in s": 1.318602 }, { "step": 176, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 4.970710142849908, "RMSE": 7.252656159084941, "R2": 0.5587960603089545, "Memory in Mb": 0.5291376113891602, "Time in s": 1.527133 }, { "step": 187, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 5.027942129925975, "RMSE": 7.276897995624471, "R2": 0.6363381045701173, "Memory in Mb": 0.5012483596801758, "Time in s": 1.7549830000000002 }, { "step": 198, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 5.049038224539579, "RMSE": 7.28413559977408, "R2": 0.7101491068659838, "Memory in Mb": 0.3717927932739258, "Time in s": 2.012416 }, { "step": 209, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 5.250417000807892, "RMSE": 7.635375364934655, "R2": 0.7374564682191251, "Memory in Mb": 0.3473329544067383, "Time in s": 2.287127 }, { "step": 220, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 5.8380227010176045, "RMSE": 8.722095838276593, "R2": 0.7000574251839753, "Memory in Mb": 0.3545808792114258, "Time in s": 2.575553 }, { "step": 231, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 6.044258003678201, "RMSE": 8.960072203538655, "R2": 0.7292489015049135, "Memory in Mb": 0.391514778137207, "Time in s": 2.875072 }, { "step": 242, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 6.276524828158362, "RMSE": 9.354066864400572, "R2": 0.7625593259413487, "Memory in Mb": 0.4183511734008789, "Time in s": 3.187566 }, { "step": 253, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 6.3739207187481774, "RMSE": 9.482128758285446, "R2": 0.7880944389945109, "Memory in Mb": 0.4399347305297851, "Time in s": 3.512786 }, { "step": 264, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 6.979732945669537, "RMSE": 10.70081988088543, "R2": 0.7534238884125567, "Memory in Mb": 0.4525842666625976, "Time in s": 3.851311 }, { "step": 275, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 7.440978636214291, "RMSE": 11.778455343325094, "R2": 0.7371253175053303, "Memory in Mb": 0.4610300064086914, "Time in s": 4.203753 }, { "step": 286, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 7.722695321089189, "RMSE": 12.251182899165162, "R2": 0.7536765505554787, "Memory in Mb": 0.4700403213500976, "Time in s": 4.570129 }, { "step": 297, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 7.706764271589622, "RMSE": 12.242915074252831, "R2": 0.7866542868859879, "Memory in Mb": 0.4733209609985351, "Time in s": 4.950063 }, { "step": 308, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 8.246398153738868, "RMSE": 13.148346181255995, "R2": 0.7808464902384371, "Memory in Mb": 0.4770059585571289, "Time in s": 5.342659 }, { "step": 319, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 9.3474227240372, "RMSE": 15.837966045238383, "R2": 0.7114408913609181, "Memory in Mb": 0.4802255630493164, "Time in s": 5.749268000000001 }, { "step": 330, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 9.81720525198044, "RMSE": 16.4984558080814, "R2": 0.732030690326682, "Memory in Mb": 0.4911470413208008, "Time in s": 6.171356000000001 }, { "step": 341, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 10.029686613445753, "RMSE": 16.618597428793866, "R2": 0.7565388422982208, "Memory in Mb": 0.496312141418457, "Time in s": 6.607662000000001 }, { "step": 352, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 10.183424974922596, "RMSE": 16.72954607175143, "R2": 0.7757182197717174, "Memory in Mb": 0.5041093826293945, "Time in s": 7.058783000000001 }, { "step": 363, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 11.087226456936444, "RMSE": 18.183293641227465, "R2": 0.7427163510168195, "Memory in Mb": 0.5065813064575195, "Time in s": 7.524030000000001 }, { "step": 374, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 11.611208342142504, "RMSE": 19.353368352464965, "R2": 0.7320664683002076, "Memory in Mb": 0.4931306838989258, "Time in s": 8.007171000000001 }, { "step": 385, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 12.01727910935522, "RMSE": 20.0211446068419, "R2": 0.7463056879958478, "Memory in Mb": 0.4681062698364258, "Time in s": 8.510702000000002 }, { "step": 396, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 12.181393533243163, "RMSE": 20.04691533881536, "R2": 0.7628481050767555, "Memory in Mb": 0.4353647232055664, "Time in s": 9.035917 }, { "step": 407, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 13.09061742270854, "RMSE": 21.647454224788547, "R2": 0.7429569103775002, "Memory in Mb": 0.4253015518188476, "Time in s": 9.583169000000002 }, { "step": 418, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 13.857583790923206, "RMSE": 23.134723844753264, "R2": 0.7244169153448246, "Memory in Mb": 0.4488153457641601, "Time in s": 10.147004 }, { "step": 429, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 14.415812868423222, "RMSE": 24.06086703427245, "R2": 0.7351096813998451, "Memory in Mb": 0.4820413589477539, "Time in s": 10.724926 }, { "step": 440, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 14.633210713365676, "RMSE": 24.14605091357361, "R2": 0.7521125932778163, "Memory in Mb": 0.5092172622680664, "Time in s": 11.318068 }, { "step": 451, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 15.133020029766048, "RMSE": 24.73830229788057, "R2": 0.7508643131645836, "Memory in Mb": 0.5367746353149414, "Time in s": 11.926425 }, { "step": 462, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 16.308165732303497, "RMSE": 27.095114472384648, "R2": 0.7192825818530082, "Memory in Mb": 0.5905351638793945, "Time in s": 12.55391 }, { "step": 473, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 17.097647362788752, "RMSE": 28.42746345262044, "R2": 0.7271490710401121, "Memory in Mb": 0.6096200942993164, "Time in s": 13.198999 }, { "step": 484, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 17.403233741388874, "RMSE": 28.60630060223112, "R2": 0.7388459944901757, "Memory in Mb": 0.6277017593383789, "Time in s": 13.862263 }, { "step": 495, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 17.845914876737442, "RMSE": 29.12415998011611, "R2": 0.7453593218363636, "Memory in Mb": 0.6518182754516602, "Time in s": 14.54413 }, { "step": 506, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 18.74953553887996, "RMSE": 30.62874049978988, "R2": 0.7265554777237875, "Memory in Mb": 0.6593713760375977, "Time in s": 15.245298000000002 }, { "step": 517, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 19.47487310339954, "RMSE": 31.618292560451803, "R2": 0.7250121198400961, "Memory in Mb": 0.6093225479125977, "Time in s": 15.967903000000002 }, { "step": 528, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 20.25384975920148, "RMSE": 32.7838221306768, "R2": 0.7341994138392889, "Memory in Mb": 0.6206216812133789, "Time in s": 16.707851 }, { "step": 539, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 20.43401222967888, "RMSE": 32.81136182644564, "R2": 0.7447469767293837, "Memory in Mb": 0.6340532302856445, "Time in s": 17.46759 }, { "step": 550, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 21.48271816680656, "RMSE": 34.486522216355176, "R2": 0.7267085961280999, "Memory in Mb": 0.6409807205200195, "Time in s": 18.246304 }, { "step": 561, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 22.214948014440758, "RMSE": 35.44362766111904, "R2": 0.7239528137855742, "Memory in Mb": 0.6374177932739258, "Time in s": 19.046772 }, { "step": 572, "track": "Regression", "model": "Bagging", "dataset": "ChickWeights", "MAE": 23.05953013824058, "RMSE": 36.58622235196899, "R2": 0.7279275728793118, "Memory in Mb": 0.6435747146606445, "Time in s": 19.865794 }, { "step": 20, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 6.585839365171216, "RMSE": 13.881516159864546, "R2": -450.9893611410228, "Memory in Mb": 0.4141368865966797, "Time in s": 0.017776 }, { "step": 40, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 4.363712565198605, "RMSE": 9.938671227284791, "R2": -38.712022235644, "Memory in Mb": 0.5953998565673828, "Time in s": 0.05778 }, { "step": 60, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 3.1246200328296143, "RMSE": 8.126568674182735, "R2": -34.79519075888522, "Memory in Mb": 0.7211894989013672, "Time in s": 0.123528 }, { "step": 80, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 2.5854221987839483, "RMSE": 7.070456887280416, "R2": -26.179962781345687, "Memory in Mb": 0.8254451751708984, "Time in s": 0.217362 }, { "step": 100, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 2.612795341566278, "RMSE": 6.441452396131832, "R2": -13.15439617190778, "Memory in Mb": 0.9287128448486328, "Time in s": 0.340609 }, { "step": 120, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 2.5650159676967723, "RMSE": 5.964319967024998, "R2": -9.294746752112973, "Memory in Mb": 0.9687213897705078, "Time in s": 0.493962 }, { "step": 140, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 2.4246087892523565, "RMSE": 5.555151474129083, "R2": -8.228790661275799, "Memory in Mb": 0.9892597198486328, "Time in s": 0.677921 }, { "step": 160, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 2.2372944440918734, "RMSE": 5.2113826313001965, "R2": -6.162524907472281, "Memory in Mb": 1.0282306671142578, "Time in s": 0.8947890000000001 }, { "step": 180, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 2.1466345389477697, "RMSE": 4.9537003451084844, "R2": -4.683842281929501, "Memory in Mb": 0.9880685806274414, "Time in s": 1.151076 }, { "step": 200, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.9892950861944356, "RMSE": 4.704683592711833, "R2": -4.14200943628533, "Memory in Mb": 0.5611734390258789, "Time in s": 1.477073 }, { "step": 220, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.8962186057938932, "RMSE": 4.499134208858052, "R2": -4.072640393025983, "Memory in Mb": 0.3967218399047851, "Time in s": 1.841739 }, { "step": 240, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.803503053095204, "RMSE": 4.314740779926486, "R2": -3.700467691841136, "Memory in Mb": 0.4504899978637695, "Time in s": 2.225753 }, { "step": 260, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.7080100607704198, "RMSE": 4.14999374436193, "R2": -3.406965132392963, "Memory in Mb": 0.5133523941040039, "Time in s": 2.631091 }, { "step": 280, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.6655932342441322, "RMSE": 4.017842470146439, "R2": -3.324861014485008, "Memory in Mb": 0.6190156936645508, "Time in s": 3.0590589999999995 }, { "step": 300, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.6385421968346507, "RMSE": 3.904974440220909, "R2": -3.01765496812087, "Memory in Mb": 0.7099161148071289, "Time in s": 3.510991 }, { "step": 320, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.5504197008133211, "RMSE": 3.781681667850968, "R2": -2.954527764504537, "Memory in Mb": 0.777043342590332, "Time in s": 3.987728 }, { "step": 340, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.5047182142648992, "RMSE": 3.6774767295200856, "R2": -2.9518368180177696, "Memory in Mb": 0.8162164688110352, "Time in s": 4.49124 }, { "step": 360, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.5167434089128324, "RMSE": 3.599404249538014, "R2": -2.816912258630976, "Memory in Mb": 0.8943338394165039, "Time in s": 5.022537 }, { "step": 380, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.47690532831993, "RMSE": 3.5095784857397434, "R2": -2.754312484791544, "Memory in Mb": 0.9456682205200196, "Time in s": 5.582067 }, { "step": 400, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.4473785178172314, "RMSE": 3.4281100357630656, "R2": -2.683273334840131, "Memory in Mb": 1.0103578567504885, "Time in s": 6.172723 }, { "step": 420, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.40955398667131, "RMSE": 3.3497394826483737, "R2": -2.633176800681623, "Memory in Mb": 0.9896020889282228, "Time in s": 6.801780999999999 }, { "step": 440, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.3766290707405415, "RMSE": 3.2780180874471507, "R2": -2.4163065189839363, "Memory in Mb": 1.0508508682250977, "Time in s": 7.462708999999999 }, { "step": 460, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.3473843223583597, "RMSE": 3.2105206765417766, "R2": -2.1076358108912725, "Memory in Mb": 1.1290063858032229, "Time in s": 8.158304 }, { "step": 480, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.3146601146346069, "RMSE": 3.145698486393554, "R2": -1.914776430829721, "Memory in Mb": 1.2007226943969729, "Time in s": 8.887782 }, { "step": 500, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.2829933656636, "RMSE": 3.084835387092109, "R2": -1.7442697801193798, "Memory in Mb": 1.2468271255493164, "Time in s": 9.6533 }, { "step": 520, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.253253159364902, "RMSE": 3.027195393916086, "R2": -1.647288417049146, "Memory in Mb": 1.2976083755493164, "Time in s": 10.456286 }, { "step": 540, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.221748892460797, "RMSE": 2.9719574458877616, "R2": -1.5422080467663055, "Memory in Mb": 1.2989130020141602, "Time in s": 11.302161 }, { "step": 560, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.2084725532442826, "RMSE": 2.924408360153415, "R2": -1.5201637785773734, "Memory in Mb": 1.2362565994262695, "Time in s": 12.194852 }, { "step": 580, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.1798260089354875, "RMSE": 2.875143807222344, "R2": -1.496217338554359, "Memory in Mb": 1.0948266983032229, "Time in s": 13.14623 }, { "step": 600, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.1697523000107772, "RMSE": 2.832108990371036, "R2": -1.3952574337441268, "Memory in Mb": 0.9711389541625975, "Time in s": 14.161435 }, { "step": 620, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.1550049446613664, "RMSE": 2.791430677298195, "R2": -1.29147514335963, "Memory in Mb": 0.9871377944946288, "Time in s": 15.218796 }, { "step": 640, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.1314798119108302, "RMSE": 2.748614104980716, "R2": -1.180190104825623, "Memory in Mb": 0.955540657043457, "Time in s": 16.316332 }, { "step": 660, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.1121913646065007, "RMSE": 2.708986615305391, "R2": -1.102550782410015, "Memory in Mb": 0.9793291091918944, "Time in s": 17.449759 }, { "step": 680, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.096472283083769, "RMSE": 2.6715401075955145, "R2": -1.0771388394715324, "Memory in Mb": 1.0325212478637695, "Time in s": 18.614745 }, { "step": 700, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.0884657542544798, "RMSE": 2.639348967980305, "R2": -1.080631470653255, "Memory in Mb": 1.1148195266723633, "Time in s": 19.813024 }, { "step": 720, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.0667544669913536, "RMSE": 2.603003384812668, "R2": -1.0681837571806945, "Memory in Mb": 1.1698732376098633, "Time in s": 21.046603 }, { "step": 740, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.0459321867530782, "RMSE": 2.5682868281355016, "R2": -1.0121733037883445, "Memory in Mb": 1.2092561721801758, "Time in s": 22.315315 }, { "step": 760, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.0276781933457848, "RMSE": 2.5353029000371494, "R2": -0.9820644398878616, "Memory in Mb": 1.2420778274536133, "Time in s": 23.623046 }, { "step": 780, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.0094276125302497, "RMSE": 2.50338787783782, "R2": -0.9411341749539492, "Memory in Mb": 1.3017473220825195, "Time in s": 24.968597 }, { "step": 800, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 1.0023537746213038, "RMSE": 2.475512975868657, "R2": -0.9153129864924484, "Memory in Mb": 1.3318758010864258, "Time in s": 26.357821 }, { "step": 820, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 0.9977235614586972, "RMSE": 2.450813157375169, "R2": -0.8978992844128302, "Memory in Mb": 1.3786516189575195, "Time in s": 27.784762 }, { "step": 840, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 0.9889333901170724, "RMSE": 2.4246168260512984, "R2": -0.8747893145143344, "Memory in Mb": 1.416356086730957, "Time in s": 29.251496 }, { "step": 860, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 0.9712423333697714, "RMSE": 2.3967734443047704, "R2": -0.8288218633529623, "Memory in Mb": 1.4480867385864258, "Time in s": 30.757563999999995 }, { "step": 880, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 0.9593965092028914, "RMSE": 2.3708401769846086, "R2": -0.7805683851951253, "Memory in Mb": 1.4688615798950195, "Time in s": 32.305297 }, { "step": 900, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 0.9500350341868696, "RMSE": 2.346029725301664, "R2": -0.7508441641708208, "Memory in Mb": 1.3691072463989258, "Time in s": 33.916341 }, { "step": 920, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 0.9362562616709212, "RMSE": 2.321054413049932, "R2": -0.7419227486050888, "Memory in Mb": 1.2137422561645508, "Time in s": 35.592854 }, { "step": 940, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 0.9293426247327622, "RMSE": 2.2986373047272863, "R2": -0.7229310397545319, "Memory in Mb": 1.2394838333129885, "Time in s": 37.31016399999999 }, { "step": 960, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 0.9223382441623138, "RMSE": 2.2770208564096435, "R2": -0.7083555493245846, "Memory in Mb": 1.2827730178833008, "Time in s": 39.06327099999999 }, { "step": 980, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 0.9155630176835056, "RMSE": 2.256277668055956, "R2": -0.7099489887647161, "Memory in Mb": 1.2986268997192385, "Time in s": 40.85878199999999 }, { "step": 1000, "track": "Regression", "model": "Bagging", "dataset": "TrumpApproval", "MAE": 0.9044154317407224, "RMSE": 2.234829366963466, "R2": -0.7058332444386559, "Memory in Mb": 1.3350114822387695, "Time in s": 42.69044199999999 }, { "step": 11, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 41.63636363636363, "RMSE": 41.64569169030137, "R2": -2231.5319148936137, "Memory in Mb": 0.0524826049804687, "Time in s": 0.006254 }, { "step": 22, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 41.31818181818181, "RMSE": 41.32960638133835, "R2": -1808.0547045951903, "Memory in Mb": 0.0595359802246093, "Time in s": 0.016967 }, { "step": 33, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 41.12121212121212, "RMSE": 41.13871582091424, "R2": -1174.393494897962, "Memory in Mb": 0.0739974975585937, "Time in s": 0.032538 }, { "step": 44, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 41.159090909090914, "RMSE": 41.17451771534076, "R2": -1333.7620984139928, "Memory in Mb": 0.0802268981933593, "Time in s": 0.0535149999999999 }, { "step": 55, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 41.5090909090909, "RMSE": 41.57075020645253, "R2": -336.3506066081568, "Memory in Mb": 0.0978660583496093, "Time in s": 0.0804889999999999 }, { "step": 66, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 42.681818181818166, "RMSE": 42.82080349691271, "R2": -153.29834830483878, "Memory in Mb": 0.121429443359375, "Time in s": 0.1147379999999999 }, { "step": 77, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 43.50649350649351, "RMSE": 43.70978671356627, "R2": -106.75487995129542, "Memory in Mb": 0.1384239196777343, "Time in s": 0.1574789999999999 }, { "step": 88, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 44.21590909090909, "RMSE": 44.43649707984724, "R2": -99.97346126163, "Memory in Mb": 0.1540603637695312, "Time in s": 0.209356 }, { "step": 99, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 45.05050505050505, "RMSE": 45.309262771858165, "R2": -86.8022342468144, "Memory in Mb": 0.1602935791015625, "Time in s": 0.271082 }, { "step": 110, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 46.16363636363636, "RMSE": 46.52487115902242, "R2": -63.64797006437341, "Memory in Mb": 0.164306640625, "Time in s": 0.3431619999999999 }, { "step": 121, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 47.21487603305785, "RMSE": 47.67304278378361, "R2": -51.27707184490422, "Memory in Mb": 0.1650009155273437, "Time in s": 0.4251659999999999 }, { "step": 132, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 48.29545454545455, "RMSE": 48.843054157105485, "R2": -43.84882422437649, "Memory in Mb": 0.165863037109375, "Time in s": 0.5168919999999999 }, { "step": 143, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 49.44055944055945, "RMSE": 50.100318941519305, "R2": -37.220279564063546, "Memory in Mb": 0.1322584152221679, "Time in s": 0.622087 }, { "step": 154, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 50.532467532467535, "RMSE": 51.29137544271156, "R2": -33.04474826644667, "Memory in Mb": 0.1404676437377929, "Time in s": 0.736412 }, { "step": 165, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 51.690909090909095, "RMSE": 52.61253451297311, "R2": -27.795548438273773, "Memory in Mb": 0.1464834213256836, "Time in s": 0.8597999999999999 }, { "step": 176, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 53.00568181818182, "RMSE": 54.11860921749895, "R2": -23.566226925646237, "Memory in Mb": 0.1528844833374023, "Time in s": 0.99286 }, { "step": 187, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 54.41176470588235, "RMSE": 55.733754017636336, "R2": -20.33250305682894, "Memory in Mb": 0.1579313278198242, "Time in s": 1.135584 }, { "step": 198, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 56.02525252525252, "RMSE": 57.635786091488654, "R2": -17.146924852486976, "Memory in Mb": 0.1600141525268554, "Time in s": 1.287864 }, { "step": 209, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 57.5645933014354, "RMSE": 59.46206220864915, "R2": -14.922837840066968, "Memory in Mb": 0.1255407333374023, "Time in s": 1.454924 }, { "step": 220, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 58.69090909090908, "RMSE": 60.81327606250582, "R2": -13.581197962556498, "Memory in Mb": 0.1323118209838867, "Time in s": 1.63074 }, { "step": 231, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 60.25541125541125, "RMSE": 62.66764529032318, "R2": -12.244451024360147, "Memory in Mb": 0.1370038986206054, "Time in s": 1.815352 }, { "step": 242, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 62.17355371900826, "RMSE": 65.06963847478845, "R2": -10.489760184397111, "Memory in Mb": 0.1415891647338867, "Time in s": 2.009009 }, { "step": 253, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 63.93675889328063, "RMSE": 67.17295239601157, "R2": -9.634560128382748, "Memory in Mb": 0.1452207565307617, "Time in s": 2.211595 }, { "step": 264, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 65.10606060606062, "RMSE": 68.57980310513724, "R2": -9.127665748505592, "Memory in Mb": 0.1458845138549804, "Time in s": 2.423132 }, { "step": 275, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 66.61454545454548, "RMSE": 70.46451073219248, "R2": -8.408339126213217, "Memory in Mb": 0.1459379196166992, "Time in s": 2.643805 }, { "step": 286, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 68.48951048951052, "RMSE": 72.8020594498525, "R2": -7.6983532427125105, "Memory in Mb": 0.1282644271850586, "Time in s": 2.877713 }, { "step": 297, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 70.55218855218858, "RMSE": 75.3669362796119, "R2": -7.08492451355157, "Memory in Mb": 0.1300420761108398, "Time in s": 3.120317 }, { "step": 308, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 72.39285714285718, "RMSE": 77.65033596401675, "R2": -6.643510181414674, "Memory in Mb": 0.1343069076538086, "Time in s": 3.37158 }, { "step": 319, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 73.45454545454551, "RMSE": 79.15086186624424, "R2": -6.206879640065647, "Memory in Mb": 0.1407041549682617, "Time in s": 3.631653 }, { "step": 330, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 75.77878787878792, "RMSE": 82.20832738177494, "R2": -5.653192449779911, "Memory in Mb": 0.1449460983276367, "Time in s": 3.900744 }, { "step": 341, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 77.92375366568919, "RMSE": 84.89106353805269, "R2": -5.352795814687307, "Memory in Mb": 0.1466054916381836, "Time in s": 4.1790140000000005 }, { "step": 352, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 80.04545454545458, "RMSE": 87.49376601169416, "R2": -5.134510311668016, "Memory in Mb": 0.1466588973999023, "Time in s": 4.46626 }, { "step": 363, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 80.99724517906337, "RMSE": 88.57562798692558, "R2": -5.105139086016474, "Memory in Mb": 0.1461553573608398, "Time in s": 4.762509 }, { "step": 374, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 82.77807486631018, "RMSE": 90.83029071422122, "R2": -4.901675845817959, "Memory in Mb": 0.1569280624389648, "Time in s": 5.06867 }, { "step": 385, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 85.1766233766234, "RMSE": 93.99517810235533, "R2": -4.591702735915359, "Memory in Mb": 0.1629590988159179, "Time in s": 5.384646 }, { "step": 396, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 87.26767676767678, "RMSE": 96.48964983485284, "R2": -4.494054297851511, "Memory in Mb": 0.1698560714721679, "Time in s": 5.710516 }, { "step": 407, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 89.00737100737103, "RMSE": 98.71879502607636, "R2": -4.345544683073043, "Memory in Mb": 0.1741170883178711, "Time in s": 6.048375 }, { "step": 418, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 90.57416267942588, "RMSE": 100.72635724110243, "R2": -4.224084264201084, "Memory in Mb": 0.1756696701049804, "Time in s": 6.396311 }, { "step": 429, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 93.12121212121215, "RMSE": 104.19735398794236, "R2": -3.967717840349581, "Memory in Mb": 0.1753263473510742, "Time in s": 6.754458 }, { "step": 440, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 95.41818181818184, "RMSE": 107.03565676064125, "R2": -3.8710119659250095, "Memory in Mb": 0.1580381393432617, "Time in s": 7.124987 }, { "step": 451, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 97.16629711751663, "RMSE": 109.07665280092142, "R2": -3.843505105397095, "Memory in Mb": 0.1671514511108398, "Time in s": 7.505263 }, { "step": 462, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 98.71645021645024, "RMSE": 111.1763643167196, "R2": -3.72620239405422, "Memory in Mb": 0.1737470626831054, "Time in s": 7.89547 }, { "step": 473, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 101.54122621564484, "RMSE": 115.2058457378686, "R2": -3.48124047566686, "Memory in Mb": 0.1785993576049804, "Time in s": 8.295795 }, { "step": 484, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 103.77066115702482, "RMSE": 117.90601559037044, "R2": -3.4365483842712585, "Memory in Mb": 0.1823682785034179, "Time in s": 8.706368 }, { "step": 495, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 106.02424242424244, "RMSE": 120.71525892518191, "R2": -3.37467008920777, "Memory in Mb": 0.1661062240600586, "Time in s": 9.13027 }, { "step": 506, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 107.31620553359684, "RMSE": 122.26004165941237, "R2": -3.356924458603192, "Memory in Mb": 0.1709508895874023, "Time in s": 9.564033 }, { "step": 517, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 109.39651837524178, "RMSE": 124.91233289427784, "R2": -3.291877964737682, "Memory in Mb": 0.1725950241088867, "Time in s": 10.007821 }, { "step": 528, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 112.36553030303028, "RMSE": 129.1106745698386, "R2": -3.1225038051323804, "Memory in Mb": 0.1781835556030273, "Time in s": 10.461944 }, { "step": 539, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 114.52504638218922, "RMSE": 131.65752925403248, "R2": -3.109734667916423, "Memory in Mb": 0.1829481124877929, "Time in s": 10.926196 }, { "step": 550, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 115.89999999999996, "RMSE": 133.35909826820617, "R2": -3.0866973064470367, "Memory in Mb": 0.1825780868530273, "Time in s": 11.400602999999998 }, { "step": 561, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 117.86452762923346, "RMSE": 135.8046463151548, "R2": -3.0526234314410727, "Memory in Mb": 0.1822462081909179, "Time in s": 11.885435 }, { "step": 572, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "ChickWeights", "MAE": 120.54020979020974, "RMSE": 139.4624607986965, "R2": -2.953338846956928, "Memory in Mb": 0.1833868026733398, "Time in s": 12.380554 }, { "step": 20, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 43.8732195, "RMSE": 43.87807788634269, "R2": -4514.954899312423, "Memory in Mb": 0.1279449462890625, "Time in s": 0.015909 }, { "step": 40, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 42.4932955, "RMSE": 42.52255283421693, "R2": -725.9491167623446, "Memory in Mb": 0.1855659484863281, "Time in s": 0.053644 }, { "step": 60, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 42.2167785, "RMSE": 42.2386240157387, "R2": -966.0073736019044, "Memory in Mb": 0.2224998474121093, "Time in s": 0.118601 }, { "step": 80, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 41.975705625, "RMSE": 41.99760868559829, "R2": -957.9655948743646, "Memory in Mb": 0.2547683715820312, "Time in s": 0.215522 }, { "step": 100, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 41.37550450000001, "RMSE": 41.410913785433536, "R2": -583.9966399141301, "Memory in Mb": 0.2853622436523437, "Time in s": 0.349036 }, { "step": 120, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.936110000000006, "RMSE": 40.97829382197767, "R2": -484.9611418859003, "Memory in Mb": 0.2942886352539062, "Time in s": 0.520816 }, { "step": 140, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.6885472857143, "RMSE": 40.72961738075088, "R2": -495.1050461477588, "Memory in Mb": 0.2989387512207031, "Time in s": 0.713599 }, { "step": 160, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.35105437500001, "RMSE": 40.39801158334292, "R2": -429.4078677932073, "Memory in Mb": 0.2328748703002929, "Time in s": 0.934381 }, { "step": 180, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.00981655555555, "RMSE": 40.06373388340122, "R2": -370.7794659133543, "Memory in Mb": 0.2508001327514648, "Time in s": 1.175315 }, { "step": 200, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.80633095, "RMSE": 39.860362966711, "R2": -368.1089073295326, "Memory in Mb": 0.1596212387084961, "Time in s": 1.445583 }, { "step": 220, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.727043136363626, "RMSE": 39.77723500009918, "R2": -395.5019807293188, "Memory in Mb": 0.1831541061401367, "Time in s": 1.734898 }, { "step": 240, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.56323079166665, "RMSE": 39.61325406766278, "R2": -395.19837684116754, "Memory in Mb": 0.1905164718627929, "Time in s": 2.043551 }, { "step": 260, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.42014538461535, "RMSE": 39.46968290441584, "R2": -397.63185900832246, "Memory in Mb": 0.2020750045776367, "Time in s": 2.371621 }, { "step": 280, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.33200189285712, "RMSE": 39.37942345737111, "R2": -414.4560159350036, "Memory in Mb": 0.2260313034057617, "Time in s": 2.720012 }, { "step": 300, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.18435719999999, "RMSE": 39.23275803924839, "R2": -404.5402138221895, "Memory in Mb": 0.2437810897827148, "Time in s": 3.088623 }, { "step": 320, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.13568690624999, "RMSE": 39.1818628962716, "R2": -423.5167725219512, "Memory in Mb": 0.2581815719604492, "Time in s": 3.477665 }, { "step": 340, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.14620944117645, "RMSE": 39.18989510023786, "R2": -447.7943063391533, "Memory in Mb": 0.2493734359741211, "Time in s": 3.892527 }, { "step": 360, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.24072974999997, "RMSE": 39.28395553300239, "R2": -453.6543473793619, "Memory in Mb": 0.2643537521362304, "Time in s": 4.328145999999999 }, { "step": 380, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.29597665789471, "RMSE": 39.33769921546023, "R2": -470.6701690846498, "Memory in Mb": 0.2747945785522461, "Time in s": 4.784845 }, { "step": 400, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.35730624999997, "RMSE": 39.39781946688104, "R2": -485.4842825426507, "Memory in Mb": 0.2898855209350586, "Time in s": 5.262664 }, { "step": 420, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.40549083333331, "RMSE": 39.44465897881697, "R2": -502.7799504226928, "Memory in Mb": 0.2975950241088867, "Time in s": 5.761624 }, { "step": 440, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.49730674999998, "RMSE": 39.53710368662846, "R2": -495.9856416828035, "Memory in Mb": 0.3090314865112304, "Time in s": 6.281948 }, { "step": 460, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.61474728260867, "RMSE": 39.65658853240579, "R2": -473.14358309219216, "Memory in Mb": 0.3255758285522461, "Time in s": 6.824272 }, { "step": 480, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.71032456249997, "RMSE": 39.75304758270976, "R2": -464.4916761787406, "Memory in Mb": 0.3411321640014648, "Time in s": 7.389190999999999 }, { "step": 500, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.80313951999997, "RMSE": 39.84667590965187, "R2": -456.8750824508669, "Memory in Mb": 0.2797002792358398, "Time in s": 7.981206999999999 }, { "step": 520, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.87354713461536, "RMSE": 39.916931033645376, "R2": -459.2932847271911, "Memory in Mb": 0.2906713485717773, "Time in s": 8.594204 }, { "step": 540, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.94649651851849, "RMSE": 39.98996046818772, "R2": -459.28610565666287, "Memory in Mb": 0.2965841293334961, "Time in s": 9.232432 }, { "step": 560, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 39.97606614285712, "RMSE": 40.018487723609816, "R2": -470.926187706672, "Memory in Mb": 0.3019857406616211, "Time in s": 9.891908 }, { "step": 580, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.00338510344825, "RMSE": 40.044755101652726, "R2": -483.2331705341176, "Memory in Mb": 0.3056249618530273, "Time in s": 10.572818 }, { "step": 600, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.07393431666663, "RMSE": 40.11569326301364, "R2": -479.5746686678817, "Memory in Mb": 0.3106412887573242, "Time in s": 11.275213 }, { "step": 620, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.1459417741935, "RMSE": 40.18827077358568, "R2": -473.96334667177865, "Memory in Mb": 0.3147268295288086, "Time in s": 11.999135999999998 }, { "step": 640, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.21943815624997, "RMSE": 40.26249426545423, "R2": -466.8085709746123, "Memory in Mb": 0.3194303512573242, "Time in s": 12.744586999999996 }, { "step": 660, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.28296777272724, "RMSE": 40.32626722721455, "R2": -464.9172853497744, "Memory in Mb": 0.3247060775756836, "Time in s": 13.511768999999996 }, { "step": 680, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.31998279411761, "RMSE": 40.36256991107017, "R2": -473.1325264408024, "Memory in Mb": 0.3289289474487304, "Time in s": 14.300919999999998 }, { "step": 700, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.31359012857138, "RMSE": 40.35509446667054, "R2": -485.40526703956544, "Memory in Mb": 0.2762861251831054, "Time in s": 15.116749 }, { "step": 720, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.31730695833329, "RMSE": 40.357915759594896, "R2": -496.1610725544049, "Memory in Mb": 0.2866239547729492, "Time in s": 15.953537 }, { "step": 740, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.36653568918915, "RMSE": 40.40711941642496, "R2": -497.0742803710164, "Memory in Mb": 0.2274045944213867, "Time in s": 16.820776 }, { "step": 760, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.40314367105261, "RMSE": 40.443256311482514, "R2": -503.3712175162706, "Memory in Mb": 0.2380895614624023, "Time in s": 17.708028 }, { "step": 780, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.44545064102563, "RMSE": 40.48534274444009, "R2": -506.6856716110208, "Memory in Mb": 0.2534551620483398, "Time in s": 18.615628 }, { "step": 800, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.47854825, "RMSE": 40.518050685964006, "R2": -512.1052117095793, "Memory in Mb": 0.2672185897827148, "Time in s": 19.543925 }, { "step": 820, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.50894034146341, "RMSE": 40.5479845946661, "R2": -518.5068774177179, "Memory in Mb": 0.2752447128295898, "Time in s": 20.493024 }, { "step": 840, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.5406558690476, "RMSE": 40.57931089736599, "R2": -524.140575335229, "Memory in Mb": 0.2841558456420898, "Time in s": 21.463054 }, { "step": 860, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.58371181395347, "RMSE": 40.62239247493601, "R2": -524.3496319016275, "Memory in Mb": 0.2900037765502929, "Time in s": 22.454245 }, { "step": 880, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.62855514772725, "RMSE": 40.66738601007716, "R2": -522.897851512946, "Memory in Mb": 0.2707319259643554, "Time in s": 23.471721 }, { "step": 900, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.664104233333326, "RMSE": 40.702738445808535, "R2": -526.020768835918, "Memory in Mb": 0.2802000045776367, "Time in s": 24.510012 }, { "step": 920, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.68274704347825, "RMSE": 40.72073961991632, "R2": -535.1540147256861, "Memory in Mb": 0.2901716232299804, "Time in s": 25.569536 }, { "step": 940, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.70972619148935, "RMSE": 40.74737437775791, "R2": -540.4099749760601, "Memory in Mb": 0.2975721359252929, "Time in s": 26.655616 }, { "step": 960, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.73400636458332, "RMSE": 40.771242977826994, "R2": -546.7118652484228, "Memory in Mb": 0.3080549240112304, "Time in s": 27.763054 }, { "step": 980, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.74031829795916, "RMSE": 40.77684015923968, "R2": -557.5026042066913, "Memory in Mb": 0.3134031295776367, "Time in s": 28.892281 }, { "step": 1000, "track": "Regression", "model": "Exponentially Weighted Average", "dataset": "TrumpApproval", "MAE": 40.75359492299998, "RMSE": 40.78950075300399, "R2": -567.2567645513548, "Memory in Mb": 0.3166418075561523, "Time in s": 30.043213999999995 }, { "step": 11, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 41.63636363636363, "RMSE": 41.64569169030137, "R2": -2231.5319148936137, "Memory in Mb": 0.0121526718139648, "Time in s": 0.028772 }, { "step": 22, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 41.31818181818181, "RMSE": 41.32960638133835, "R2": -1808.0547045951903, "Memory in Mb": 0.0121526718139648, "Time in s": 0.079044 }, { "step": 33, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 41.12121212121212, "RMSE": 41.13871582091424, "R2": -1174.393494897962, "Memory in Mb": 0.0121526718139648, "Time in s": 0.149857 }, { "step": 44, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 41.159090909090914, "RMSE": 41.17451771534076, "R2": -1333.7620984139928, "Memory in Mb": 0.0121526718139648, "Time in s": 0.237747 }, { "step": 55, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 41.5090909090909, "RMSE": 41.57075020645253, "R2": -336.3506066081568, "Memory in Mb": 0.0121526718139648, "Time in s": 0.338425 }, { "step": 66, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 42.681818181818166, "RMSE": 42.82080349691271, "R2": -153.29834830483878, "Memory in Mb": 0.0121526718139648, "Time in s": 0.452041 }, { "step": 77, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 43.46441536424646, "RMSE": 43.6630525281676, "R2": -106.5245816691109, "Memory in Mb": 0.0121526718139648, "Time in s": 0.578307 }, { "step": 88, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 43.36686847531974, "RMSE": 43.58986852756654, "R2": -96.16251088961316, "Memory in Mb": 0.0121526718139648, "Time in s": 0.71715 }, { "step": 99, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 39.3777319762956, "RMSE": 41.29293125499619, "R2": -71.92610223487543, "Memory in Mb": 0.0121526718139648, "Time in s": 0.8686729999999999 }, { "step": 110, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 36.38865389064824, "RMSE": 39.46494228501369, "R2": -45.51654802750055, "Memory in Mb": 0.0121526718139648, "Time in s": 1.032976 }, { "step": 121, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 33.47571311046551, "RMSE": 37.6638192516392, "R2": -31.6297858502766, "Memory in Mb": 0.0121526718139648, "Time in s": 1.209623 }, { "step": 132, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 30.829458151969483, "RMSE": 36.06523958622657, "R2": -23.452489437409387, "Memory in Mb": 0.0121526718139648, "Time in s": 1.398231 }, { "step": 143, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 28.6940047418964, "RMSE": 34.66464981164902, "R2": -17.297279097398025, "Memory in Mb": 0.0121526718139648, "Time in s": 1.59888 }, { "step": 154, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 26.901670019158168, "RMSE": 33.42439644535526, "R2": -13.457346308406352, "Memory in Mb": 0.0121526718139648, "Time in s": 1.811498 }, { "step": 165, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 25.73601455188179, "RMSE": 32.42918896219868, "R2": -9.940044331027543, "Memory in Mb": 0.0121526718139648, "Time in s": 2.036514 }, { "step": 176, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 24.44416894616589, "RMSE": 31.465121114844862, "R2": -7.304318935113031, "Memory in Mb": 0.0121526718139648, "Time in s": 2.273516 }, { "step": 187, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 23.31106527863985, "RMSE": 30.560727675640003, "R2": -5.414053903472148, "Memory in Mb": 0.0121526718139648, "Time in s": 2.522216 }, { "step": 198, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 22.2497659881735, "RMSE": 29.72926965926448, "R2": -3.828220321961205, "Memory in Mb": 0.0121526718139648, "Time in s": 2.782587 }, { "step": 209, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 21.58385771370322, "RMSE": 29.10991604615937, "R2": -2.8161237021822814, "Memory in Mb": 0.0121526718139648, "Time in s": 3.05463 }, { "step": 220, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 21.489125733317938, "RMSE": 28.89967848441583, "R2": -2.2929294700983545, "Memory in Mb": 0.0121526718139648, "Time in s": 3.338483 }, { "step": 231, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 20.96077526896472, "RMSE": 28.36167354440183, "R2": -1.7127571457874735, "Memory in Mb": 0.0121526718139648, "Time in s": 3.633999 }, { "step": 242, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 20.684837308385998, "RMSE": 27.97322591752617, "R2": -1.123436519018493, "Memory in Mb": 0.0121526718139648, "Time in s": 3.941181 }, { "step": 253, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 20.10836609318901, "RMSE": 27.433189641281587, "R2": -0.7737126718723288, "Memory in Mb": 0.0121526718139648, "Time in s": 4.259926 }, { "step": 264, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 20.477468707260805, "RMSE": 27.77140109557264, "R2": -0.6607814047377214, "Memory in Mb": 0.012312889099121, "Time in s": 4.590346 }, { "step": 275, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 20.61134029899391, "RMSE": 28.056502395486245, "R2": -0.491554549366604, "Memory in Mb": 0.012312889099121, "Time in s": 4.932228 }, { "step": 286, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 20.562403371381592, "RMSE": 27.861367163045813, "R2": -0.2739563786996055, "Memory in Mb": 0.012312889099121, "Time in s": 5.285550000000001 }, { "step": 297, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 20.2802158532438, "RMSE": 27.63742758295081, "R2": -0.0872000961905188, "Memory in Mb": 0.012312889099121, "Time in s": 5.650314000000001 }, { "step": 308, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 20.449355350398, "RMSE": 27.920149137510645, "R2": 0.0118073081415535, "Memory in Mb": 0.012312889099121, "Time in s": 6.026518000000001 }, { "step": 319, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 21.50134169290969, "RMSE": 30.009678165732637, "R2": -0.0359973595319296, "Memory in Mb": 0.012312889099121, "Time in s": 6.414170000000001 }, { "step": 330, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 21.657358056011915, "RMSE": 30.050226639054536, "R2": 0.1110159573580076, "Memory in Mb": 0.012312889099121, "Time in s": 6.813245000000001 }, { "step": 341, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 21.886687938329302, "RMSE": 30.333453058468624, "R2": 0.1888808568866784, "Memory in Mb": 0.012312889099121, "Time in s": 7.223789000000001 }, { "step": 352, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 21.886047000767118, "RMSE": 30.34044931799507, "R2": 0.2623171341711791, "Memory in Mb": 0.012312889099121, "Time in s": 7.645758000000001 }, { "step": 363, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 22.895757506339034, "RMSE": 32.0447958992957, "R2": 0.2009350122171253, "Memory in Mb": 0.012312889099121, "Time in s": 8.07951 }, { "step": 374, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 23.75249563906416, "RMSE": 33.838912051163845, "R2": 0.1808815149406113, "Memory in Mb": 0.012312889099121, "Time in s": 8.524693000000001 }, { "step": 385, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 24.560900349589296, "RMSE": 34.753482086388026, "R2": 0.2355843412503995, "Memory in Mb": 0.012312889099121, "Time in s": 8.981311000000002 }, { "step": 396, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 24.352453583923488, "RMSE": 34.473609026370774, "R2": 0.2986981406442135, "Memory in Mb": 0.012312889099121, "Time in s": 9.449373 }, { "step": 407, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 25.719275464870663, "RMSE": 37.04357441923364, "R2": 0.2473067090757558, "Memory in Mb": 0.012312889099121, "Time in s": 9.928858000000002 }, { "step": 418, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 27.096550121003176, "RMSE": 39.902565812758986, "R2": 0.1801666848023049, "Memory in Mb": 0.012312889099121, "Time in s": 10.419752000000004 }, { "step": 429, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 28.343681876579897, "RMSE": 42.0624752869508, "R2": 0.1904695440990398, "Memory in Mb": 0.012312889099121, "Time in s": 10.922067000000002 }, { "step": 440, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 29.341897763641, "RMSE": 43.65194027092424, "R2": 0.1898427093039769, "Memory in Mb": 0.012312889099121, "Time in s": 11.435807000000002 }, { "step": 451, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 30.67273802938304, "RMSE": 45.6370688200433, "R2": 0.1521253661768283, "Memory in Mb": 0.012312889099121, "Time in s": 11.960959000000004 }, { "step": 462, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 32.56224145473062, "RMSE": 49.915337115223885, "R2": 0.0473016837570096, "Memory in Mb": 0.012312889099121, "Time in s": 12.497734000000005 }, { "step": 473, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 34.43415680949522, "RMSE": 53.78695495416363, "R2": 0.0232056621878617, "Memory in Mb": 0.012312889099121, "Time in s": 13.045956000000004 }, { "step": 484, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 37.59302308486845, "RMSE": 59.43178585545712, "R2": -0.1272256336981969, "Memory in Mb": 0.012312889099121, "Time in s": 13.605608000000004 }, { "step": 495, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 39.81029832190851, "RMSE": 63.2563754686467, "R2": -0.2012394142017446, "Memory in Mb": 0.012312889099121, "Time in s": 14.176690000000004 }, { "step": 506, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 40.81849028215024, "RMSE": 64.7117163856453, "R2": -0.2206096222811289, "Memory in Mb": 0.012312889099121, "Time in s": 14.759208000000005 }, { "step": 517, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 42.30053541895924, "RMSE": 66.69347450894223, "R2": -0.2234984190364006, "Memory in Mb": 0.012312889099121, "Time in s": 15.353157000000005 }, { "step": 528, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 43.87998520264807, "RMSE": 69.22658128427689, "R2": -0.1851751428384946, "Memory in Mb": 0.012312889099121, "Time in s": 15.958328000000003 }, { "step": 539, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 45.090482136166365, "RMSE": 70.91807128614899, "R2": -0.1924391171188431, "Memory in Mb": 0.012312889099121, "Time in s": 16.574693000000003 }, { "step": 550, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 46.16603381063717, "RMSE": 72.79977252028388, "R2": -0.2178315347358042, "Memory in Mb": 0.012312889099121, "Time in s": 17.202244000000004 }, { "step": 561, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 47.99895001321041, "RMSE": 75.49864048778444, "R2": -0.2525216922711382, "Memory in Mb": 0.012312889099121, "Time in s": 17.841166000000005 }, { "step": 572, "track": "Regression", "model": "River MLP", "dataset": "ChickWeights", "MAE": 49.57826542612398, "RMSE": 77.90262570405233, "R2": -0.2335409846027114, "Memory in Mb": 0.012312889099121, "Time in s": 18.491295000000004 }, { "step": 20, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 30.45103241731707, "RMSE": 33.23585723529438, "R2": -2590.0045530336465, "Memory in Mb": 0.0131101608276367, "Time in s": 0.03648 }, { "step": 40, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 18.3406114455606, "RMSE": 24.1628558112126, "R2": -233.72636807636488, "Memory in Mb": 0.0131101608276367, "Time in s": 0.100456 }, { "step": 60, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 14.012302795940927, "RMSE": 20.27429916426714, "R2": -221.7932161673039, "Memory in Mb": 0.0131101608276367, "Time in s": 0.190991 }, { "step": 80, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 11.49107264681655, "RMSE": 17.720640796103456, "R2": -169.73114207921216, "Memory in Mb": 0.0131101608276367, "Time in s": 0.307239 }, { "step": 100, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 9.726608796116103, "RMSE": 15.913172800750536, "R2": -85.38479390162912, "Memory in Mb": 0.0131101608276367, "Time in s": 0.4491740000000001 }, { "step": 120, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 8.642897473622819, "RMSE": 14.610205599232696, "R2": -60.77410396737057, "Memory in Mb": 0.0131101608276367, "Time in s": 0.6162740000000001 }, { "step": 140, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 7.627861449957184, "RMSE": 13.547130531753504, "R2": -53.88423494401591, "Memory in Mb": 0.0131101608276367, "Time in s": 0.8076440000000001 }, { "step": 160, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 6.825616478903957, "RMSE": 12.68640242718137, "R2": -41.44604107616888, "Memory in Mb": 0.0131101608276367, "Time in s": 1.023068 }, { "step": 180, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 6.298325880816026, "RMSE": 11.99455373608459, "R2": -32.32351025206219, "Memory in Mb": 0.0131101608276367, "Time in s": 1.262663 }, { "step": 200, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 5.791221405645649, "RMSE": 11.389261045241726, "R2": -29.134439780883504, "Memory in Mb": 0.0131101608276367, "Time in s": 1.526002 }, { "step": 220, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 5.429217208457164, "RMSE": 10.877504011291329, "R2": -28.650681734644422, "Memory in Mb": 0.0131101608276367, "Time in s": 1.812923 }, { "step": 240, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 5.060396678997669, "RMSE": 10.421476408956162, "R2": -26.4214333861576, "Memory in Mb": 0.0131101608276367, "Time in s": 2.123256 }, { "step": 260, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 4.7577579662422185, "RMSE": 10.01970369652003, "R2": -24.68943115642662, "Memory in Mb": 0.013350486755371, "Time in s": 2.456738 }, { "step": 280, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 4.47898479527949, "RMSE": 9.659781964354623, "R2": -23.99890538466576, "Memory in Mb": 0.013350486755371, "Time in s": 2.813161 }, { "step": 300, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 4.231628573868652, "RMSE": 9.33546881214548, "R2": -21.961936464609707, "Memory in Mb": 0.013350486755371, "Time in s": 3.192823 }, { "step": 320, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 4.032288217093912, "RMSE": 9.046394584789834, "R2": -21.629541054113563, "Memory in Mb": 0.013350486755371, "Time in s": 3.5954460000000004 }, { "step": 340, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 3.8351551756309497, "RMSE": 8.779241117397504, "R2": -21.522318216666985, "Memory in Mb": 0.013350486755371, "Time in s": 4.021045 }, { "step": 360, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 3.660607443401045, "RMSE": 8.536652519215579, "R2": -20.469707840891584, "Memory in Mb": 0.013350486755371, "Time in s": 4.469678 }, { "step": 380, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 3.505270605120577, "RMSE": 8.311598150636895, "R2": -20.056664379019765, "Memory in Mb": 0.013350486755371, "Time in s": 4.941134 }, { "step": 400, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 3.360453882251005, "RMSE": 8.10307441673556, "R2": -19.578991923208985, "Memory in Mb": 0.013350486755371, "Time in s": 5.435716 }, { "step": 420, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 3.230603986740656, "RMSE": 7.909485894846834, "R2": -19.256340082684435, "Memory in Mb": 0.013350486755371, "Time in s": 5.953156 }, { "step": 440, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 3.1198347345540465, "RMSE": 7.731010347257149, "R2": -18.002320884204543, "Memory in Mb": 0.013350486755371, "Time in s": 6.493473 }, { "step": 460, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 3.010353198494384, "RMSE": 7.562877110682495, "R2": -16.244605442867506, "Memory in Mb": 0.013350486755371, "Time in s": 7.056611999999999 }, { "step": 480, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 2.9023580604284582, "RMSE": 7.404341650720478, "R2": -15.148937801753288, "Memory in Mb": 0.013350486755371, "Time in s": 7.642589999999999 }, { "step": 500, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 2.8120368518109427, "RMSE": 7.256642134427339, "R2": -14.185679409391112, "Memory in Mb": 0.013350486755371, "Time in s": 8.251631 }, { "step": 520, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 2.722217494708863, "RMSE": 7.11705765703134, "R2": -13.632593906904136, "Memory in Mb": 0.013350486755371, "Time in s": 8.883484 }, { "step": 540, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 2.6379600337769933, "RMSE": 6.984812005374008, "R2": -13.042206620144157, "Memory in Mb": 0.013350486755371, "Time in s": 9.537691 }, { "step": 560, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 2.573532085936036, "RMSE": 6.862931118690264, "R2": -12.879442173523902, "Memory in Mb": 0.013350486755371, "Time in s": 10.214296 }, { "step": 580, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 2.508294944253365, "RMSE": 6.745457437445754, "R2": -12.739978855164816, "Memory in Mb": 0.013350486755371, "Time in s": 10.913296 }, { "step": 600, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 2.4431260057234407, "RMSE": 6.633435680824833, "R2": -12.140422111767563, "Memory in Mb": 0.013350486755371, "Time in s": 11.634954 }, { "step": 620, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 2.386700775516181, "RMSE": 6.528113194197335, "R2": -11.53247390884172, "Memory in Mb": 0.013350486755371, "Time in s": 12.379039999999998 }, { "step": 640, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 2.3242014075410804, "RMSE": 6.426013651213371, "R2": -10.916538218303476, "Memory in Mb": 0.013350486755371, "Time in s": 13.145560999999995 }, { "step": 660, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 2.2685968162113417, "RMSE": 6.328883008296775, "R2": -10.475904112331508, "Memory in Mb": 0.013350486755371, "Time in s": 13.934486999999995 }, { "step": 680, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 2.2077966601853354, "RMSE": 6.235306598260896, "R2": -10.31508330333358, "Memory in Mb": 0.013350486755371, "Time in s": 14.745848999999998 }, { "step": 700, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 2.1581493026656715, "RMSE": 6.146460408814674, "R2": -10.283704638807178, "Memory in Mb": 0.013350486755371, "Time in s": 15.579853999999996 }, { "step": 720, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 2.1027567473920863, "RMSE": 6.060643545524585, "R2": -10.211846444382044, "Memory in Mb": 0.013350486755371, "Time in s": 16.436290999999997 }, { "step": 740, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 2.051121816682194, "RMSE": 5.978350933609188, "R2": -9.90287777753909, "Memory in Mb": 0.013350486755371, "Time in s": 17.315177999999996 }, { "step": 760, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 2.003155134641025, "RMSE": 5.899358540561457, "R2": -9.731678337792127, "Memory in Mb": 0.013350486755371, "Time in s": 18.216514 }, { "step": 780, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 1.9581628436412764, "RMSE": 5.823548668044576, "R2": -9.504483044737295, "Memory in Mb": 0.013350486755371, "Time in s": 19.140319 }, { "step": 800, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 1.920522972774301, "RMSE": 5.751090425279772, "R2": -9.337362153707344, "Memory in Mb": 0.013350486755371, "Time in s": 20.086783 }, { "step": 820, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 1.884378546616626, "RMSE": 5.681435320930898, "R2": -9.199265318679966, "Memory in Mb": 0.013350486755371, "Time in s": 21.055682 }, { "step": 840, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 1.8462172344878476, "RMSE": 5.613649762186833, "R2": -9.049787223051387, "Memory in Mb": 0.013350486755371, "Time in s": 22.047027 }, { "step": 860, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 1.8114873001009923, "RMSE": 5.548504609880171, "R2": -8.800976301633217, "Memory in Mb": 0.013350486755371, "Time in s": 23.060786 }, { "step": 880, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 1.7737427907909609, "RMSE": 5.485176730961097, "R2": -8.530931568707373, "Memory in Mb": 0.013350486755371, "Time in s": 24.096958 }, { "step": 900, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 1.7378742216236305, "RMSE": 5.423968591721732, "R2": -8.358684442608821, "Memory in Mb": 0.013350486755371, "Time in s": 25.155795 }, { "step": 920, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 1.7058202733924563, "RMSE": 5.364926267836746, "R2": -8.30648673172487, "Memory in Mb": 0.013350486755371, "Time in s": 26.237104 }, { "step": 940, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 1.6771033983092818, "RMSE": 5.307938337650396, "R2": -8.187106100071555, "Memory in Mb": 0.013350486755371, "Time in s": 27.340904 }, { "step": 960, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 1.6470899020587193, "RMSE": 5.252615019014566, "R2": -8.09065943244505, "Memory in Mb": 0.013350486755371, "Time in s": 28.467203 }, { "step": 980, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 1.6179664800066769, "RMSE": 5.198922142498095, "R2": -8.078721464420347, "Memory in Mb": 0.013350486755371, "Time in s": 29.615952 }, { "step": 1000, "track": "Regression", "model": "River MLP", "dataset": "TrumpApproval", "MAE": 1.591389315944533, "RMSE": 5.1470018023734205, "R2": -8.048080908594342, "Memory in Mb": 0.013350486755371, "Time in s": 30.787287 }, { "step": 11, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 4.664574314574316, "RMSE": 12.7079745317607, "R2": -206.87879383707747, "Memory in Mb": 0.0004901885986328, "Time in s": 0.002154 }, { "step": 22, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 2.767694704637076, "RMSE": 9.018587183866767, "R2": -85.14025986830408, "Memory in Mb": 0.0004901885986328, "Time in s": 0.005944 }, { "step": 33, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 2.3093367298127023, "RMSE": 7.420500566500976, "R2": -37.24267181629702, "Memory in Mb": 0.0004901885986328, "Time in s": 0.010037 }, { "step": 44, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 1.892363968348808, "RMSE": 6.441521936619904, "R2": -31.668094594906044, "Memory in Mb": 0.0004901885986328, "Time in s": 0.014469 }, { "step": 55, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 2.1129412159858934, "RMSE": 6.114058653243701, "R2": -6.297346571779499, "Memory in Mb": 0.0004901885986328, "Time in s": 0.019181 }, { "step": 66, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 2.832849782567835, "RMSE": 6.236602142425367, "R2": -2.2730130120415795, "Memory in Mb": 0.0004901885986328, "Time in s": 0.024182 }, { "step": 77, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 3.4069290990236856, "RMSE": 6.402381882180361, "R2": -1.3118663438824, "Memory in Mb": 0.0004901885986328, "Time in s": 0.029453 }, { "step": 88, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 3.650377971160808, "RMSE": 6.321189272940957, "R2": -1.043267371916866, "Memory in Mb": 0.0004901885986328, "Time in s": 0.034986 }, { "step": 99, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 4.035631404360372, "RMSE": 6.4483291916176695, "R2": -0.7783857772357967, "Memory in Mb": 0.0004901885986328, "Time in s": 0.040781 }, { "step": 110, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 4.693189868957898, "RMSE": 7.0697740144659305, "R2": -0.4927792786841307, "Memory in Mb": 0.0004901885986328, "Time in s": 0.046845 }, { "step": 121, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 5.274396860168236, "RMSE": 7.6542276724395, "R2": -0.3476225254437259, "Memory in Mb": 0.0004901885986328, "Time in s": 0.053171 }, { "step": 132, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 5.875758254207378, "RMSE": 8.194624755054596, "R2": -0.2624191661321591, "Memory in Mb": 0.0004901885986328, "Time in s": 0.05976 }, { "step": 143, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 6.530760796045927, "RMSE": 8.870097879563003, "R2": -0.1980355424044948, "Memory in Mb": 0.0004901885986328, "Time in s": 0.066612 }, { "step": 154, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 7.121466111912466, "RMSE": 9.458403141043558, "R2": -0.1577027852151795, "Memory in Mb": 0.0004901885986328, "Time in s": 0.073726 }, { "step": 165, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 7.772438504082036, "RMSE": 10.375670403553157, "R2": -0.1198999930450892, "Memory in Mb": 0.0004901885986328, "Time in s": 0.081109 }, { "step": 176, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 8.565827130563894, "RMSE": 11.410434180005833, "R2": -0.0920676568626532, "Memory in Mb": 0.0004901885986328, "Time in s": 0.088752 }, { "step": 187, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 9.429958588641576, "RMSE": 12.495061319237752, "R2": -0.0722153171628203, "Memory in Mb": 0.0004901885986328, "Time in s": 0.096665 }, { "step": 198, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 10.47731537859646, "RMSE": 13.900491647656429, "R2": -0.0555502703757588, "Memory in Mb": 0.0004901885986328, "Time in s": 0.104851 }, { "step": 209, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 11.43172675762076, "RMSE": 15.229123619635446, "R2": -0.0444565128716372, "Memory in Mb": 0.0004901885986328, "Time in s": 0.1133 }, { "step": 220, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 11.97432098008114, "RMSE": 16.22368260926648, "R2": -0.0377560869847111, "Memory in Mb": 0.0004901885986328, "Time in s": 0.122025 }, { "step": 231, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 12.9382196746461, "RMSE": 17.489503190785292, "R2": -0.0315781972827118, "Memory in Mb": 0.0004901885986328, "Time in s": 0.131017 }, { "step": 242, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 14.229204186206864, "RMSE": 19.43725798629848, "R2": -0.0252367718674193, "Memory in Mb": 0.0004901885986328, "Time in s": 0.140272 }, { "step": 253, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 15.339413196393396, "RMSE": 20.82023831254592, "R2": -0.0216497893038387, "Memory in Mb": 0.0004901885986328, "Time in s": 0.149788 }, { "step": 264, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 15.948617107030818, "RMSE": 21.75817315507082, "R2": -0.0194401851240946, "Memory in Mb": 0.0004901885986328, "Time in s": 0.159572 }, { "step": 275, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 16.794155127707494, "RMSE": 23.16724301729152, "R2": -0.0169996193237813, "Memory in Mb": 0.0004901885986328, "Time in s": 0.169617 }, { "step": 286, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 17.990009992534457, "RMSE": 24.865985915258104, "R2": -0.0147547133955299, "Memory in Mb": 0.0004901885986328, "Time in s": 0.17992 }, { "step": 297, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 19.34919450213405, "RMSE": 26.67620929760368, "R2": -0.0128904565600072, "Memory in Mb": 0.0004901885986328, "Time in s": 0.190491 }, { "step": 308, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 20.46881241431745, "RMSE": 28.248013022827838, "R2": -0.011537481517321, "Memory in Mb": 0.0004901885986328, "Time in s": 0.201321 }, { "step": 319, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 20.993702124162965, "RMSE": 29.63814114349949, "R2": -0.0105036731193923, "Memory in Mb": 0.0004901885986328, "Time in s": 0.212414 }, { "step": 330, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 22.586872779548436, "RMSE": 32.01796640002603, "R2": -0.0092202379520505, "Memory in Mb": 0.0004901885986328, "Time in s": 0.223765 }, { "step": 341, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 23.97345887210737, "RMSE": 33.821533603903084, "R2": -0.0083877019037323, "Memory in Mb": 0.0004901885986328, "Time in s": 0.235368 }, { "step": 352, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 25.315991788770976, "RMSE": 35.461698606860665, "R2": -0.0077313021586467, "Memory in Mb": 0.0004901885986328, "Time in s": 0.247225 }, { "step": 363, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 25.615062978866305, "RMSE": 35.981300981590465, "R2": -0.0074437490312051, "Memory in Mb": 0.0004901885986328, "Time in s": 0.259337 }, { "step": 374, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 26.673321526932543, "RMSE": 37.51836715700961, "R2": -0.0069358461242559, "Memory in Mb": 0.0004901885986328, "Time in s": 0.271713 }, { "step": 385, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 28.27694482780972, "RMSE": 39.8753298933956, "R2": -0.0063325109838794, "Memory in Mb": 0.0004901885986328, "Time in s": 0.2843549999999999 }, { "step": 396, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 29.55612496209691, "RMSE": 41.28848705945016, "R2": -0.0059801818919071, "Memory in Mb": 0.0004901885986328, "Time in s": 0.2972059999999999 }, { "step": 407, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 30.56167711268285, "RMSE": 42.81802042618151, "R2": -0.0056467231500465, "Memory in Mb": 0.0004901885986328, "Time in s": 0.3102509999999999 }, { "step": 418, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 31.39346669137945, "RMSE": 44.18765357092498, "R2": -0.0053697143301307, "Memory in Mb": 0.0004901885986328, "Time in s": 0.3234889999999999 }, { "step": 429, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 33.10612890637694, "RMSE": 46.865579751152914, "R2": -0.0049663660706051, "Memory in Mb": 0.0004901885986328, "Time in s": 0.3369199999999999 }, { "step": 440, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 34.54914638861108, "RMSE": 48.61167278858254, "R2": -0.0047161238549726, "Memory in Mb": 0.0004901885986328, "Time in s": 0.3505489999999999 }, { "step": 451, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 35.43263419295921, "RMSE": 49.67507127970072, "R2": -0.0045536938071879, "Memory in Mb": 0.0004901885986328, "Time in s": 0.3643729999999999 }, { "step": 462, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 36.308550382896186, "RMSE": 51.2507761435036, "R2": -0.0043573774895468, "Memory in Mb": 0.0004901885986328, "Time in s": 0.3783909999999999 }, { "step": 473, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 38.26330298063241, "RMSE": 54.53225049728104, "R2": -0.0040516612048955, "Memory in Mb": 0.0004901885986328, "Time in s": 0.3926029999999999 }, { "step": 484, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 39.59866234800828, "RMSE": 56.08659790201894, "R2": -0.0039023944795495, "Memory in Mb": 0.0004901885986328, "Time in s": 0.4070059999999999 }, { "step": 495, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 40.94697327298068, "RMSE": 57.823326559810994, "R2": -0.0037535911132069, "Memory in Mb": 0.0004901885986328, "Time in s": 0.4215999999999999 }, { "step": 506, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 41.42384714758024, "RMSE": 58.67984594201592, "R2": -0.0036652347211194, "Memory in Mb": 0.0004901885986328, "Time in s": 0.4363849999999999 }, { "step": 517, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 42.72663002099646, "RMSE": 60.40151056768402, "R2": -0.0035345422299792, "Memory in Mb": 0.0004901885986328, "Time in s": 0.4513639999999999 }, { "step": 528, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 44.77321528369677, "RMSE": 63.69509749878913, "R2": -0.0033415055563215, "Memory in Mb": 0.0004901885986328, "Time in s": 0.4665329999999999 }, { "step": 539, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 45.99579764939489, "RMSE": 65.0494992510053, "R2": -0.003252609562637, "Memory in Mb": 0.0004901885986328, "Time in s": 0.4818929999999999 }, { "step": 550, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 46.57020777663759, "RMSE": 66.07332710234044, "R2": -0.0031815200825582, "Memory in Mb": 0.0004901885986328, "Time in s": 0.4974459999999999 }, { "step": 561, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 47.75825760640621, "RMSE": 67.5643396193493, "R2": -0.0030950009187136, "Memory in Mb": 0.0004901885986328, "Time in s": 0.5131919999999999 }, { "step": 572, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "ChickWeights", "MAE": 49.49138874897682, "RMSE": 70.24569214117749, "R2": -0.0029719424061886, "Memory in Mb": 0.0004901885986328, "Time in s": 0.5291269999999999 }, { "step": 20, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 2.695184981652336, "RMSE": 9.807184976514188, "R2": -224.6021011118197, "Memory in Mb": 0.0004901885986328, "Time in s": 0.003379 }, { "step": 40, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 2.3994713447037435, "RMSE": 7.102066178895935, "R2": -19.27845129783118, "Memory in Mb": 0.0004901885986328, "Time in s": 0.0081789999999999 }, { "step": 60, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.8170744682035584, "RMSE": 5.815253847056423, "R2": -17.329373299766118, "Memory in Mb": 0.0004901885986328, "Time in s": 0.0135909999999999 }, { "step": 80, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.604995404573344, "RMSE": 5.081770494168446, "R2": -13.040545957103586, "Memory in Mb": 0.0004901885986328, "Time in s": 0.0195849999999999 }, { "step": 100, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.824259078948539, "RMSE": 4.70488333223354, "R2": -6.5512954222403845, "Memory in Mb": 0.0004901885986328, "Time in s": 0.0262549999999999 }, { "step": 120, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.918744608116588, "RMSE": 4.412336880489357, "R2": -4.634185300646759, "Memory in Mb": 0.0004901885986328, "Time in s": 0.033502 }, { "step": 140, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.8761207739327503, "RMSE": 4.13187920011476, "R2": -4.105616799680584, "Memory in Mb": 0.0004901885986328, "Time in s": 0.041316 }, { "step": 160, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.961232939518506, "RMSE": 3.976173487274506, "R2": -3.1695661963674864, "Memory in Mb": 0.0004901885986328, "Time in s": 0.0496949999999999 }, { "step": 180, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 2.066134597500757, "RMSE": 3.873731518767916, "R2": -2.4756944369169624, "Memory in Mb": 0.0004901885986328, "Time in s": 0.0586379999999999 }, { "step": 200, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 2.051125997923389, "RMSE": 3.731810291394655, "R2": -2.23527456693896, "Memory in Mb": 0.0004901885986328, "Time in s": 0.0682329999999999 }, { "step": 220, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.94095193468414, "RMSE": 3.56902990398404, "R2": -2.19210047340805, "Memory in Mb": 0.0004901885986328, "Time in s": 0.078397 }, { "step": 240, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.9366756524315063, "RMSE": 3.4612902974772624, "R2": -2.024876884626847, "Memory in Mb": 0.0004901885986328, "Time in s": 0.089124 }, { "step": 260, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.9250039777458068, "RMSE": 3.363327951159923, "R2": -1.8945640461454525, "Memory in Mb": 0.0004901885986328, "Time in s": 0.1004139999999999 }, { "step": 280, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.8726934920539136, "RMSE": 3.257010428159885, "R2": -1.8420037280027224, "Memory in Mb": 0.0004901885986328, "Time in s": 0.11227 }, { "step": 300, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.8907476896224935, "RMSE": 3.1958821895815714, "R2": -1.6910252267675163, "Memory in Mb": 0.0004901885986328, "Time in s": 0.124747 }, { "step": 320, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.819623890420079, "RMSE": 3.103812605138666, "R2": -1.663886258690169, "Memory in Mb": 0.0004901885986328, "Time in s": 0.137792 }, { "step": 340, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.7396293145937214, "RMSE": 3.014220627768389, "R2": -1.654906383755708, "Memory in Mb": 0.0004901885986328, "Time in s": 0.151284 }, { "step": 360, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.7350691203787965, "RMSE": 2.9569384317632506, "R2": -1.5759385016835008, "Memory in Mb": 0.0004901885986328, "Time in s": 0.165202 }, { "step": 380, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6987131960417108, "RMSE": 2.8893997308323693, "R2": -1.5446951110541192, "Memory in Mb": 0.0004901885986328, "Time in s": 0.179547 }, { "step": 400, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.673610627740774, "RMSE": 2.82935583501861, "R2": -1.5089937655143242, "Memory in Mb": 0.0004901885986328, "Time in s": 0.194363 }, { "step": 420, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6410137122925974, "RMSE": 2.7701802079251965, "R2": -1.484737486096575, "Memory in Mb": 0.0004901885986328, "Time in s": 0.209602 }, { "step": 440, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6565972573555454, "RMSE": 2.7427790467379385, "R2": -1.391750010744973, "Memory in Mb": 0.0004901885986328, "Time in s": 0.225268 }, { "step": 460, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.699464840115161, "RMSE": 2.73946740401384, "R2": -1.2626191030939884, "Memory in Mb": 0.0004901885986328, "Time in s": 0.241356 }, { "step": 480, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.7224824441896145, "RMSE": 2.7219018737730583, "R2": -1.182307732575659, "Memory in Mb": 0.0004901885986328, "Time in s": 0.257864 }, { "step": 500, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.7446092142173422, "RMSE": 2.70580354422956, "R2": -1.1113262021905803, "Memory in Mb": 0.0004901885986328, "Time in s": 0.274789 }, { "step": 520, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.7464998751860934, "RMSE": 2.677192702589883, "R2": -1.0705208906620065, "Memory in Mb": 0.0004901885986328, "Time in s": 0.292197 }, { "step": 540, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.7535492786865423, "RMSE": 2.653885630983747, "R2": -1.027170706279252, "Memory in Mb": 0.0004901885986328, "Time in s": 0.310025 }, { "step": 560, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.7201019899937544, "RMSE": 2.614359234374483, "R2": -1.0141103337708768, "Memory in Mb": 0.0004901885986328, "Time in s": 0.328271 }, { "step": 580, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6887559504032663, "RMSE": 2.5757257291728384, "R2": -1.0033760803823184, "Memory in Mb": 0.0004901885986328, "Time in s": 0.346933 }, { "step": 600, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.701917368353294, "RMSE": 2.561424763732869, "R2": -0.9592753712060648, "Memory in Mb": 0.0004901885986328, "Time in s": 0.366058 }, { "step": 620, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.7178157166185173, "RMSE": 2.551346895968156, "R2": -0.9142580419512064, "Memory in Mb": 0.0004901885986328, "Time in s": 0.38561 }, { "step": 640, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.7365901196485038, "RMSE": 2.545046385321895, "R2": -0.8692105635365064, "Memory in Mb": 0.0004901885986328, "Time in s": 0.405582 }, { "step": 660, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.7465677425181807, "RMSE": 2.532051562790666, "R2": -0.8368676529707118, "Memory in Mb": 0.0004901885986328, "Time in s": 0.425968 }, { "step": 680, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.731617734826669, "RMSE": 2.504226186170861, "R2": -0.8251107974736909, "Memory in Mb": 0.0004901885986328, "Time in s": 0.446783 }, { "step": 700, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6973720107412231, "RMSE": 2.47026789197972, "R2": -0.8225927549994396, "Memory in Mb": 0.0004901885986328, "Time in s": 0.468073 }, { "step": 720, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6698372433333928, "RMSE": 2.4400355004771077, "R2": -0.81732226470892, "Memory in Mb": 0.0004901885986328, "Time in s": 0.489788 }, { "step": 740, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6732482399922957, "RMSE": 2.425592833263792, "R2": -0.7947920429290933, "Memory in Mb": 0.0004901885986328, "Time in s": 0.511921 }, { "step": 760, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6653913599894004, "RMSE": 2.404136439714782, "R2": -0.7822814452716051, "Memory in Mb": 0.0004901885986328, "Time in s": 0.53447 }, { "step": 780, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6644612180457288, "RMSE": 2.387561393188575, "R2": -0.7656652158374817, "Memory in Mb": 0.0004901885986328, "Time in s": 0.557436 }, { "step": 800, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6556359332933146, "RMSE": 2.368497267913513, "R2": -0.7532954885990883, "Memory in Mb": 0.0004901885986328, "Time in s": 0.580851 }, { "step": 820, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6452077788467467, "RMSE": 2.348678653798561, "R2": -0.7430103139622937, "Memory in Mb": 0.0004901885986328, "Time in s": 0.604682 }, { "step": 840, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6374623223784903, "RMSE": 2.3305035344735936, "R2": -0.7320713255917544, "Memory in Mb": 0.0004901885986328, "Time in s": 0.6289220000000001 }, { "step": 860, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6419505315856449, "RMSE": 2.320208013716276, "R2": -0.7138439732116804, "Memory in Mb": 0.0004901885986328, "Time in s": 0.653572 }, { "step": 880, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6490002164922652, "RMSE": 2.3126155324510744, "R2": -0.6941855677649247, "Memory in Mb": 0.0004901885986328, "Time in s": 0.6786340000000001 }, { "step": 900, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6474991175923384, "RMSE": 2.299197536504521, "R2": -0.6816400531907807, "Memory in Mb": 0.0004901885986328, "Time in s": 0.704114 }, { "step": 920, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6301006788336792, "RMSE": 2.2779225390149764, "R2": -0.6777843948800273, "Memory in Mb": 0.0004901885986328, "Time in s": 0.730046 }, { "step": 940, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6221876471839871, "RMSE": 2.262378737250057, "R2": -0.6690049120995847, "Memory in Mb": 0.0004901885986328, "Time in s": 0.7563869999999999 }, { "step": 960, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.6124120493571743, "RMSE": 2.245866476718547, "R2": -0.6619276404267609, "Memory in Mb": 0.0004901885986328, "Time in s": 0.7831509999999999 }, { "step": 980, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.5867001120604314, "RMSE": 2.223758235975506, "R2": -0.661013659831075, "Memory in Mb": 0.0004901885986328, "Time in s": 0.810322 }, { "step": 1000, "track": "Regression", "model": "[baseline] Mean predictor", "dataset": "TrumpApproval", "MAE": 1.5681359363812415, "RMSE": 2.2037391763141216, "R2": -0.6587014308970958, "Memory in Mb": 0.0004901885986328, "Time in s": 0.8379 } ] }, "params": [ { "name": "models", "select": { "type": "point", "fields": [ "model" ] }, "bind": "legend" }, { "name": "Dataset", "value": "ChickWeights", "bind": { "input": "select", "options": [ "ChickWeights", "TrumpApproval" ] } }, { "name": "grid", "select": "interval", "bind": "scales" } ], "transform": [ { "filter": { "field": "dataset", "equal": { "expr": "Dataset" } } } ], "repeat": { "row": [ "MAE", "RMSE", "R2", "Memory in Mb", "Time in s" ] }, "spec": { "width": "container", "mark": "line", "encoding": { "x": { "field": "step", "type": "quantitative", "axis": { "titleFontSize": 18, "labelFontSize": 18, "title": "Instance" } }, "y": { "field": { "repeat": "row" }, "type": "quantitative", "axis": { "titleFontSize": 18, "labelFontSize": 18 } }, "color": { "field": "model", "type": "ordinal", "scale": { "scheme": "category20b" }, "title": "Models", "legend": { "titleFontSize": 18, "labelFontSize": 18, "labelLimit": 500 } }, "opacity": { "condition": { "param": "models", "value": 1 }, "value": 0.2 } } } }

Datasets

ChickWeights

Chick weights along time.

The stream contains 578 items and 3 features. The goal is to predict the weight of each chick along time, according to the diet the chick is on. The data is ordered by time and then by chick.

Name  ChickWeights                                                 
Task  Regression

Samples 578
Features 3
Sparse False
Path /home/kulbach/projects/river/river/datasets/chick-weights.csv

TrumpApproval

Donald Trump approval ratings.

This dataset was obtained by reshaping the data used by FiveThirtyEight for analyzing Donald Trump's approval ratings. It contains 5 features, which are approval ratings collected by 5 polling agencies. The target is the approval rating from FiveThirtyEight's model. The goal of this task is to see if we can reproduce FiveThirtyEight's model.

Name  TrumpApproval                                                    
Task  Regression

Samples 1,001
Features 6
Sparse False
Path /home/kulbach/projects/river/river/datasets/trump_approval.csv.gz

Models

Linear Regression

Pipeline (
  StandardScaler (
    with_std=True
  ),
  LinearRegression (
    optimizer=SGD (
      lr=Constant (
        learning_rate=0.01
      )
    )
    loss=Squared ()
    l2=0.
    l1=0.
    intercept_init=0.
    intercept_lr=Constant (
      learning_rate=0.01
    )
    clip_gradient=1e+12
    initializer=Zeros ()
  )
)

Linear Regression with l1 regularization

Pipeline (
  StandardScaler (
    with_std=True
  ),
  LinearRegression (
    optimizer=SGD (
      lr=Constant (
        learning_rate=0.01
      )
    )
    loss=Squared ()
    l2=0.
    l1=1.
    intercept_init=0.
    intercept_lr=Constant (
      learning_rate=0.01
    )
    clip_gradient=1e+12
    initializer=Zeros ()
  )
)

Linear Regression with l2 regularization

Pipeline (
  StandardScaler (
    with_std=True
  ),
  LinearRegression (
    optimizer=SGD (
      lr=Constant (
        learning_rate=0.01
      )
    )
    loss=Squared ()
    l2=1.
    l1=0.
    intercept_init=0.
    intercept_lr=Constant (
      learning_rate=0.01
    )
    clip_gradient=1e+12
    initializer=Zeros ()
  )
)

Passive-Aggressive Regressor, mode 1

Pipeline (
  StandardScaler (
    with_std=True
  ),
  PARegressor (
    C=1.
    mode=1
    eps=0.1
    learn_intercept=True
  )
)

Passive-Aggressive Regressor, mode 2

Pipeline (
  StandardScaler (
    with_std=True
  ),
  PARegressor (
    C=1.
    mode=2
    eps=0.1
    learn_intercept=True
  )
)

k-Nearest Neighbors

Pipeline (
  StandardScaler (
    with_std=True
  ),
  KNNRegressor (
    n_neighbors=5
    window_size=100
    aggregation_method="mean"
    min_distance_keep=0.
    distance_func=functools.partial(, p=2)
  )
)

Hoeffding Tree

Pipeline (
  StandardScaler (
    with_std=True
  ),
  HoeffdingTreeRegressor (
    grace_period=200
    max_depth=inf
    delta=1e-07
    tau=0.05
    leaf_prediction="adaptive"
    leaf_model=LinearRegression (
      optimizer=SGD (
        lr=Constant (
          learning_rate=0.01
        )
      )
      loss=Squared ()
      l2=0.
      l1=0.
      intercept_init=0.
      intercept_lr=Constant (
        learning_rate=0.01
      )
      clip_gradient=1e+12
      initializer=Zeros ()
    )
    model_selector_decay=0.95
    nominal_attributes=None
    splitter=TEBSTSplitter (
      digits=1
    )
    min_samples_split=5
    binary_split=False
    max_size=500.
    memory_estimate_period=1000000
    stop_mem_management=False
    remove_poor_attrs=False
    merit_preprune=True
  )
)

Hoeffding Adaptive Tree

Pipeline (
  StandardScaler (
    with_std=True
  ),
  HoeffdingAdaptiveTreeRegressor (
    grace_period=200
    max_depth=inf
    delta=1e-07
    tau=0.05
    leaf_prediction="adaptive"
    leaf_model=LinearRegression (
      optimizer=SGD (
        lr=Constant (
          learning_rate=0.01
        )
      )
      loss=Squared ()
      l2=0.
      l1=0.
      intercept_init=0.
      intercept_lr=Constant (
        learning_rate=0.01
      )
      clip_gradient=1e+12
      initializer=Zeros ()
    )
    model_selector_decay=0.95
    nominal_attributes=None
    splitter=TEBSTSplitter (
      digits=1
    )
    min_samples_split=5
    bootstrap_sampling=True
    drift_window_threshold=300
    drift_detector=ADWIN (
      delta=0.002
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    switch_significance=0.05
    binary_split=False
    max_size=500.
    memory_estimate_period=1000000
    stop_mem_management=False
    remove_poor_attrs=False
    merit_preprune=True
    seed=42
  )
)

Stochastic Gradient Tree

SGTRegressor (
  delta=1e-07
  grace_period=200
  init_pred=0.
  max_depth=inf
  lambda_value=0.1
  gamma=1.
  nominal_attributes=[]
  feature_quantizer=StaticQuantizer (
    n_bins=64
    warm_start=100
    buckets=None
  )
)

Adaptive Random Forest

Pipeline (
  StandardScaler (
    with_std=True
  ),
  []
)

Adaptive Model Rules

Pipeline (
  StandardScaler (
    with_std=True
  ),
  AMRules (
    n_min=200
    delta=1e-07
    tau=0.05
    pred_type="adaptive"
    pred_model=LinearRegression (
      optimizer=SGD (
        lr=Constant (
          learning_rate=0.01
        )
      )
      loss=Squared ()
      l2=0.
      l1=0.
      intercept_init=0.
      intercept_lr=Constant (
        learning_rate=0.01
      )
      clip_gradient=1e+12
      initializer=Zeros ()
    )
    splitter=TEBSTSplitter (
      digits=1
    )
    drift_detector=ADWIN (
      delta=0.002
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    fading_factor=0.99
    anomaly_threshold=-0.75
    m_min=30
    ordered_rule_set=True
    min_samples_split=5
  )
)

Streaming Random Patches

Pipeline (
  StandardScaler (
    with_std=True
  ),
  SRPRegressor (
    model=HoeffdingTreeRegressor (
      grace_period=50
      max_depth=inf
      delta=0.01
      tau=0.05
      leaf_prediction="adaptive"
      leaf_model=LinearRegression (
        optimizer=SGD (
          lr=Constant (
            learning_rate=0.01
          )
        )
        loss=Squared ()
        l2=0.
        l1=0.
        intercept_init=0.
        intercept_lr=Constant (
          learning_rate=0.01
        )
        clip_gradient=1e+12
        initializer=Zeros ()
      )
      model_selector_decay=0.95
      nominal_attributes=None
      splitter=TEBSTSplitter (
        digits=1
      )
      min_samples_split=5
      binary_split=False
      max_size=500.
      memory_estimate_period=1000000
      stop_mem_management=False
      remove_poor_attrs=False
      merit_preprune=True
    )
    n_models=10
    subspace_size=0.6
    training_method="patches"
    lam=6
    drift_detector=ADWIN (
      delta=1e-05
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    warning_detector=ADWIN (
      delta=0.0001
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    disable_detector="off"
    disable_weighted_vote=True
    drift_detection_criteria="error"
    aggregation_method="mean"
    seed=42
    metric=MAE ()
  )
)

Bagging

Pipeline (
  StandardScaler (
    with_std=True
  ),
  [HoeffdingAdaptiveTreeRegressor (
    grace_period=200
    max_depth=inf
    delta=1e-07
    tau=0.05
    leaf_prediction="adaptive"
    leaf_model=LinearRegression (
      optimizer=SGD (
        lr=Constant (
          learning_rate=0.01
        )
      )
      loss=Squared ()
      l2=0.
      l1=0.
      intercept_init=0.
      intercept_lr=Constant (
        learning_rate=0.01
      )
      clip_gradient=1e+12
      initializer=Zeros ()
    )
    model_selector_decay=0.95
    nominal_attributes=None
    splitter=TEBSTSplitter (
      digits=1
    )
    min_samples_split=5
    bootstrap_sampling=False
    drift_window_threshold=300
    drift_detector=ADWIN (
      delta=0.002
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    switch_significance=0.05
    binary_split=False
    max_size=500.
    memory_estimate_period=1000000
    stop_mem_management=False
    remove_poor_attrs=False
    merit_preprune=True
    seed=None
  ), HoeffdingAdaptiveTreeRegressor (
    grace_period=200
    max_depth=inf
    delta=1e-07
    tau=0.05
    leaf_prediction="adaptive"
    leaf_model=LinearRegression (
      optimizer=SGD (
        lr=Constant (
          learning_rate=0.01
        )
      )
      loss=Squared ()
      l2=0.
      l1=0.
      intercept_init=0.
      intercept_lr=Constant (
        learning_rate=0.01
      )
      clip_gradient=1e+12
      initializer=Zeros ()
    )
    model_selector_decay=0.95
    nominal_attributes=None
    splitter=TEBSTSplitter (
      digits=1
    )
    min_samples_split=5
    bootstrap_sampling=False
    drift_window_threshold=300
    drift_detector=ADWIN (
      delta=0.002
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    switch_significance=0.05
    binary_split=False
    max_size=500.
    memory_estimate_period=1000000
    stop_mem_management=False
    remove_poor_attrs=False
    merit_preprune=True
    seed=None
  ), HoeffdingAdaptiveTreeRegressor (
    grace_period=200
    max_depth=inf
    delta=1e-07
    tau=0.05
    leaf_prediction="adaptive"
    leaf_model=LinearRegression (
      optimizer=SGD (
        lr=Constant (
          learning_rate=0.01
        )
      )
      loss=Squared ()
      l2=0.
      l1=0.
      intercept_init=0.
      intercept_lr=Constant (
        learning_rate=0.01
      )
      clip_gradient=1e+12
      initializer=Zeros ()
    )
    model_selector_decay=0.95
    nominal_attributes=None
    splitter=TEBSTSplitter (
      digits=1
    )
    min_samples_split=5
    bootstrap_sampling=False
    drift_window_threshold=300
    drift_detector=ADWIN (
      delta=0.002
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    switch_significance=0.05
    binary_split=False
    max_size=500.
    memory_estimate_period=1000000
    stop_mem_management=False
    remove_poor_attrs=False
    merit_preprune=True
    seed=None
  ), HoeffdingAdaptiveTreeRegressor (
    grace_period=200
    max_depth=inf
    delta=1e-07
    tau=0.05
    leaf_prediction="adaptive"
    leaf_model=LinearRegression (
      optimizer=SGD (
        lr=Constant (
          learning_rate=0.01
        )
      )
      loss=Squared ()
      l2=0.
      l1=0.
      intercept_init=0.
      intercept_lr=Constant (
        learning_rate=0.01
      )
      clip_gradient=1e+12
      initializer=Zeros ()
    )
    model_selector_decay=0.95
    nominal_attributes=None
    splitter=TEBSTSplitter (
      digits=1
    )
    min_samples_split=5
    bootstrap_sampling=False
    drift_window_threshold=300
    drift_detector=ADWIN (
      delta=0.002
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    switch_significance=0.05
    binary_split=False
    max_size=500.
    memory_estimate_period=1000000
    stop_mem_management=False
    remove_poor_attrs=False
    merit_preprune=True
    seed=None
  ), HoeffdingAdaptiveTreeRegressor (
    grace_period=200
    max_depth=inf
    delta=1e-07
    tau=0.05
    leaf_prediction="adaptive"
    leaf_model=LinearRegression (
      optimizer=SGD (
        lr=Constant (
          learning_rate=0.01
        )
      )
      loss=Squared ()
      l2=0.
      l1=0.
      intercept_init=0.
      intercept_lr=Constant (
        learning_rate=0.01
      )
      clip_gradient=1e+12
      initializer=Zeros ()
    )
    model_selector_decay=0.95
    nominal_attributes=None
    splitter=TEBSTSplitter (
      digits=1
    )
    min_samples_split=5
    bootstrap_sampling=False
    drift_window_threshold=300
    drift_detector=ADWIN (
      delta=0.002
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    switch_significance=0.05
    binary_split=False
    max_size=500.
    memory_estimate_period=1000000
    stop_mem_management=False
    remove_poor_attrs=False
    merit_preprune=True
    seed=None
  ), HoeffdingAdaptiveTreeRegressor (
    grace_period=200
    max_depth=inf
    delta=1e-07
    tau=0.05
    leaf_prediction="adaptive"
    leaf_model=LinearRegression (
      optimizer=SGD (
        lr=Constant (
          learning_rate=0.01
        )
      )
      loss=Squared ()
      l2=0.
      l1=0.
      intercept_init=0.
      intercept_lr=Constant (
        learning_rate=0.01
      )
      clip_gradient=1e+12
      initializer=Zeros ()
    )
    model_selector_decay=0.95
    nominal_attributes=None
    splitter=TEBSTSplitter (
      digits=1
    )
    min_samples_split=5
    bootstrap_sampling=False
    drift_window_threshold=300
    drift_detector=ADWIN (
      delta=0.002
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    switch_significance=0.05
    binary_split=False
    max_size=500.
    memory_estimate_period=1000000
    stop_mem_management=False
    remove_poor_attrs=False
    merit_preprune=True
    seed=None
  ), HoeffdingAdaptiveTreeRegressor (
    grace_period=200
    max_depth=inf
    delta=1e-07
    tau=0.05
    leaf_prediction="adaptive"
    leaf_model=LinearRegression (
      optimizer=SGD (
        lr=Constant (
          learning_rate=0.01
        )
      )
      loss=Squared ()
      l2=0.
      l1=0.
      intercept_init=0.
      intercept_lr=Constant (
        learning_rate=0.01
      )
      clip_gradient=1e+12
      initializer=Zeros ()
    )
    model_selector_decay=0.95
    nominal_attributes=None
    splitter=TEBSTSplitter (
      digits=1
    )
    min_samples_split=5
    bootstrap_sampling=False
    drift_window_threshold=300
    drift_detector=ADWIN (
      delta=0.002
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    switch_significance=0.05
    binary_split=False
    max_size=500.
    memory_estimate_period=1000000
    stop_mem_management=False
    remove_poor_attrs=False
    merit_preprune=True
    seed=None
  ), HoeffdingAdaptiveTreeRegressor (
    grace_period=200
    max_depth=inf
    delta=1e-07
    tau=0.05
    leaf_prediction="adaptive"
    leaf_model=LinearRegression (
      optimizer=SGD (
        lr=Constant (
          learning_rate=0.01
        )
      )
      loss=Squared ()
      l2=0.
      l1=0.
      intercept_init=0.
      intercept_lr=Constant (
        learning_rate=0.01
      )
      clip_gradient=1e+12
      initializer=Zeros ()
    )
    model_selector_decay=0.95
    nominal_attributes=None
    splitter=TEBSTSplitter (
      digits=1
    )
    min_samples_split=5
    bootstrap_sampling=False
    drift_window_threshold=300
    drift_detector=ADWIN (
      delta=0.002
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    switch_significance=0.05
    binary_split=False
    max_size=500.
    memory_estimate_period=1000000
    stop_mem_management=False
    remove_poor_attrs=False
    merit_preprune=True
    seed=None
  ), HoeffdingAdaptiveTreeRegressor (
    grace_period=200
    max_depth=inf
    delta=1e-07
    tau=0.05
    leaf_prediction="adaptive"
    leaf_model=LinearRegression (
      optimizer=SGD (
        lr=Constant (
          learning_rate=0.01
        )
      )
      loss=Squared ()
      l2=0.
      l1=0.
      intercept_init=0.
      intercept_lr=Constant (
        learning_rate=0.01
      )
      clip_gradient=1e+12
      initializer=Zeros ()
    )
    model_selector_decay=0.95
    nominal_attributes=None
    splitter=TEBSTSplitter (
      digits=1
    )
    min_samples_split=5
    bootstrap_sampling=False
    drift_window_threshold=300
    drift_detector=ADWIN (
      delta=0.002
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    switch_significance=0.05
    binary_split=False
    max_size=500.
    memory_estimate_period=1000000
    stop_mem_management=False
    remove_poor_attrs=False
    merit_preprune=True
    seed=None
  ), HoeffdingAdaptiveTreeRegressor (
    grace_period=200
    max_depth=inf
    delta=1e-07
    tau=0.05
    leaf_prediction="adaptive"
    leaf_model=LinearRegression (
      optimizer=SGD (
        lr=Constant (
          learning_rate=0.01
        )
      )
      loss=Squared ()
      l2=0.
      l1=0.
      intercept_init=0.
      intercept_lr=Constant (
        learning_rate=0.01
      )
      clip_gradient=1e+12
      initializer=Zeros ()
    )
    model_selector_decay=0.95
    nominal_attributes=None
    splitter=TEBSTSplitter (
      digits=1
    )
    min_samples_split=5
    bootstrap_sampling=False
    drift_window_threshold=300
    drift_detector=ADWIN (
      delta=0.002
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    switch_significance=0.05
    binary_split=False
    max_size=500.
    memory_estimate_period=1000000
    stop_mem_management=False
    remove_poor_attrs=False
    merit_preprune=True
    seed=None
  )]
)

Exponentially Weighted Average

Pipeline (
  StandardScaler (
    with_std=True
  ),
  [LinearRegression (
    optimizer=SGD (
      lr=Constant (
        learning_rate=0.01
      )
    )
    loss=Squared ()
    l2=0.
    l1=0.
    intercept_init=0.
    intercept_lr=Constant (
      learning_rate=0.01
    )
    clip_gradient=1e+12
    initializer=Zeros ()
  ), HoeffdingAdaptiveTreeRegressor (
    grace_period=200
    max_depth=inf
    delta=1e-07
    tau=0.05
    leaf_prediction="adaptive"
    leaf_model=LinearRegression (
      optimizer=SGD (
        lr=Constant (
          learning_rate=0.01
        )
      )
      loss=Squared ()
      l2=0.
      l1=0.
      intercept_init=0.
      intercept_lr=Constant (
        learning_rate=0.01
      )
      clip_gradient=1e+12
      initializer=Zeros ()
    )
    model_selector_decay=0.95
    nominal_attributes=None
    splitter=TEBSTSplitter (
      digits=1
    )
    min_samples_split=5
    bootstrap_sampling=True
    drift_window_threshold=300
    drift_detector=ADWIN (
      delta=0.002
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    switch_significance=0.05
    binary_split=False
    max_size=500.
    memory_estimate_period=1000000
    stop_mem_management=False
    remove_poor_attrs=False
    merit_preprune=True
    seed=None
  ), KNNRegressor (
    n_neighbors=5
    window_size=100
    aggregation_method="mean"
    min_distance_keep=0.
    distance_func=functools.partial(, p=2)
  ), AMRules (
    n_min=200
    delta=1e-07
    tau=0.05
    pred_type="adaptive"
    pred_model=LinearRegression (
      optimizer=SGD (
        lr=Constant (
          learning_rate=0.01
        )
      )
      loss=Squared ()
      l2=0.
      l1=0.
      intercept_init=0.
      intercept_lr=Constant (
        learning_rate=0.01
      )
      clip_gradient=1e+12
      initializer=Zeros ()
    )
    splitter=TEBSTSplitter (
      digits=1
    )
    drift_detector=ADWIN (
      delta=0.002
      clock=32
      max_buckets=5
      min_window_length=5
      grace_period=10
    )
    fading_factor=0.99
    anomaly_threshold=-0.75
    m_min=30
    ordered_rule_set=True
    min_samples_split=5
  )]
)

River MLP

Pipeline (
  StandardScaler (
    with_std=True
  ),
  MLPRegressor (
    hidden_dims=(5,)
    activations=(, , )
    loss=Squared ()
    optimizer=SGD (
      lr=Constant (
        learning_rate=0.001
      )
    )
    seed=42
  )
)

[baseline] Mean predictor

StatisticRegressor (
  statistic=Mean ()
)

Environment

Python implementation: CPython
Python version       : 3.9.17
IPython version      : 8.15.0

river       : 0.19.0
numpy       : 1.25.2
scikit-learn: 1.3.0
pandas      : 2.1.0
scipy       : 1.11.2

Compiler    : GCC 11.3.0
OS          : Linux
Release     : 5.15.0-1041-azure
Machine     : x86_64
Processor   : x86_64
CPU cores   : 2
Architecture: 64bit