0.4.1 - 2019-10-23¶
base¶
- Tests are now much more extensive, thanks mostly to the newly added estimator tags.
compose¶
- Added
compose.Renamer
.
datasets¶
- Added
fetch_kdd99_http
. - Added
fetch_sms
. - Added
fetch_trec07p
.
ensemble¶
- Removed
ensemble.HedgeBinaryClassifier
because it's performance was subpar. - Removed
ensemble.GroupRegressor
, as this should be a special case ofensemble.StackingRegressor
.
feature_extraction¶
- Fixed a bug where
feature_extraction.CountVectorizer
andfeature_extraction.TFIDFVectorizer
couldn't be pickled.
linear_model¶
linear_model.LogisticRegression
andlinear_model.LinearRegression
now have anintercept_lr
parameter.
metrics¶
- Metrics can now be composed using the
+
operator, which is useful for evaluating multiple metrics at the same time. - Added
metrics.Rolling
, which eliminates the need for a specific rolling implementation for each metric. - Each metric can now be passed a
sample_weight
argument. - Added
metrics.WeightedF1
. - Added
metrics.WeightedFBeta
. - Added
metrics.WeightedPrecision
. - Added
metrics.WeightedRecall
.
neighbors¶
- Added
neighbors.KNeighborsRegressor
. - Added
neighbors.KNeighborsClassifier
.
optim¶
- Added
optim.AdaMax
. - The
optim
module has been reorganized into submodules; namelyoptim.schedulers
,optim.initializers
, andoptim.losses
. The top-level now only contains optimizers. Some classes have been renamed accordingly. See the documentation for details. - Renamed
optim.VanillaSGD
tooptim.SGD
.
stats¶
- Added
stats.IQR
. - Added
stats.RollingIQR
. - Cythonized
stats.Mean
andstats.Var
.
stream¶
- Added
stream.shuffle
. stream.iter_csv
now hasfraction
andseed
parameters to sample rows, deterministically or not.- Renamed
stream.iter_numpy
tostream.iter_array
. stream.iter_csv
can now read from gzipped files.
time_series¶
time_series.Detrender
now has awindow_size
parameter for detrending with a rolling mean.
tree¶
- Added
tree.RandomForestClassifier
.
utils¶
- Fixed a bug where
utils.dot
could take longer than necessary.