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River
online-ml/river
Home
Getting started
Getting started
In a nutshell
Installation
User guide
User guide
Reading data
Model evaluation
Pipelines
Feature extraction
Hyperparameter tuning
Mini-batching
Incremental decision trees in river: the Hoeffding Tree case
API reference
API reference
Overview
anomaly
anomaly
AnomalyDetector
ConstantThresholder
HalfSpaceTrees
OneClassSVM
QuantileThresholder
base
base
Base
Classifier
Clusterer
DriftDetector
Ensemble
Estimator
MiniBatchClassifier
MiniBatchRegressor
MultiOutputMixin
Regressor
SupervisedTransformer
Transformer
Wrapper
WrapperEnsemble
cluster
cluster
CluStream
DBSTREAM
DenStream
KMeans
STREAMKMeans
compat
compat
PyTorch2RiverClassifier
PyTorch2RiverRegressor
River2SKLClassifier
River2SKLClusterer
River2SKLRegressor
River2SKLTransformer
SKL2RiverClassifier
SKL2RiverRegressor
convert_river_to_sklearn
convert_sklearn_to_river
compose
compose
Discard
FuncTransformer
Grouper
Pipeline
Renamer
Select
SelectType
TargetTransformRegressor
TransformerProduct
TransformerUnion
datasets
datasets
AirlinePassengers
Bananas
Bikes
ChickWeights
CreditCard
Elec2
HTTP
Higgs
ImageSegments
Insects
Keystroke
MaliciousURL
MovieLens100K
Music
Phishing
Restaurants
SMSSpam
SMTP
SolarFlare
TREC07
Taxis
TrumpApproval
drift
drift
ADWIN
DDM
EDDM
HDDM_A
HDDM_W
KSWIN
PageHinkley
dummy
dummy
NoChangeClassifier
PriorClassifier
StatisticRegressor
ensemble
ensemble
ADWINBaggingClassifier
AdaBoostClassifier
AdaptiveRandomForestClassifier
AdaptiveRandomForestRegressor
BaggingClassifier
BaggingRegressor
EWARegressor
LeveragingBaggingClassifier
SRPClassifier
SRPRegressor
StackingClassifier
VotingClassifier
evaluate
evaluate
Track
load_binary_clf_tracks
progressive_val_score
facto
facto
FFMClassifier
FFMRegressor
FMClassifier
FMRegressor
FwFMClassifier
FwFMRegressor
HOFMClassifier
HOFMRegressor
feature_extraction
feature_extraction
Agg
BagOfWords
Lagger
PolynomialExtender
RBFSampler
TFIDF
TargetAgg
TargetLagger
feature_selection
feature_selection
PoissonInclusion
SelectKBest
VarianceThreshold
imblearn
imblearn
HardSamplingClassifier
HardSamplingRegressor
RandomOverSampler
RandomSampler
RandomUnderSampler
linear_model
linear_model
ALMAClassifier
LinearRegression
LogisticRegression
PAClassifier
PARegressor
Perceptron
SoftmaxRegression
metrics
metrics
Accuracy
AdjustedMutualInfo
AdjustedRand
BalancedAccuracy
BinaryMetric
ClassificationMetric
ClassificationReport
CohenKappa
Completeness
ConfusionMatrix
CrossEntropy
ExactMatch
ExampleF1
ExampleFBeta
ExamplePrecision
ExampleRecall
F1
FBeta
FowlkesMallows
GeometricMean
Hamming
HammingLoss
Homogeneity
Jaccard
KappaM
KappaT
LogLoss
MAE
MCC
MSE
MacroF1
MacroFBeta
MacroPrecision
MacroRecall
MatthewsCorrCoef
Metric
Metrics
MicroF1
MicroFBeta
MicroPrecision
MicroRecall
MultiClassMetric
MultiFBeta
MultiLabelConfusionMatrix
MultiOutputClassificationMetric
MultiOutputRegressionMetric
MutualInfo
NormalizedMutualInfo
PairConfusionMatrix
Precision
PrevalenceThreshold
Purity
Q0
Q2
R2
RMSE
RMSLE
ROCAUC
Rand
Recall
RegressionMetric
RegressionMultiOutput
Rolling
SMAPE
SorensenDice
TimeRolling
VBeta
VariationInfo
WeightedF1
WeightedFBeta
WeightedPrecision
WeightedRecall
WrapperMetric
cluster
cluster
BIC
BallHall
CalinskiHarabasz
Cohesion
DaviesBouldin
GD43
GD53
Hartigan
IIndex
InternalMetric
MSSTD
PS
R2
RMSSTD
SD
SSB
SSW
Separation
Silhouette
WB
XieBeni
Xu
model_selection
model_selection
EpsilonGreedyRegressor
GreedyRegressor
ModelSelector
SuccessiveHalvingClassifier
SuccessiveHalvingRegressor
UCBRegressor
multiclass
multiclass
OneVsOneClassifier
OneVsRestClassifier
OutputCodeClassifier
multioutput
multioutput
ClassifierChain
MonteCarloClassifierChain
ProbabilisticClassifierChain
RegressorChain
naive_bayes
naive_bayes
BernoulliNB
ComplementNB
GaussianNB
MultinomialNB
neighbors
neighbors
KNNADWINClassifier
KNNClassifier
KNNRegressor
SAMKNNClassifier
neural_net
neural_net
MLPRegressor
activations
activations
Identity
ReLU
Sigmoid
optim
optim
AMSGrad
AdaBound
AdaDelta
AdaGrad
AdaMax
Adam
Averager
FTRLProximal
Momentum
Nadam
NesterovMomentum
Optimizer
RMSProp
SGD
initializers
initializers
Constant
Normal
Zeros
losses
losses
Absolute
BinaryFocalLoss
BinaryLoss
Cauchy
CrossEntropy
EpsilonInsensitiveHinge
Hinge
Huber
Log
MultiClassLoss
Poisson
Quantile
RegressionLoss
Squared
schedulers
schedulers
Constant
InverseScaling
Optimal
Scheduler
preprocessing
preprocessing
AdaptiveStandardScaler
Binarizer
FeatureHasher
LDA
MaxAbsScaler
MinMaxScaler
Normalizer
OneHotEncoder
PredClipper
PreviousImputer
RobustScaler
StandardScaler
StatImputer
TargetStandardScaler
proba
proba
Gaussian
Multinomial
reco
reco
Baseline
BiasedMF
FunkMF
RandomNormal
SurpriseWrapper
rules
rules
AMRules
stats
stats
AbsMax
AutoCorr
BayesianMean
Bivariate
Count
Cov
EWMean
EWVar
Entropy
IQR
Kurtosis
Link
MAD
Max
Mean
Min
Mode
NUnique
PeakToPeak
PearsonCorr
Quantile
RollingAbsMax
RollingCov
RollingIQR
RollingMax
RollingMean
RollingMin
RollingMode
RollingPeakToPeak
RollingPearsonCorr
RollingQuantile
RollingSEM
RollingSum
RollingVar
SEM
Shift
Skew
Sum
Univariate
Var
stream
stream
Cache
iter_arff
iter_array
iter_csv
iter_libsvm
iter_pandas
iter_sklearn_dataset
iter_sql
iter_vaex
shuffle
simulate_qa
synth
synth
Agrawal
AnomalySine
ConceptDriftStream
Friedman
FriedmanDrift
Hyperplane
LED
LEDDrift
Logical
Mixed
Mv
Planes2D
RandomRBF
RandomRBFDrift
RandomTree
SEA
STAGGER
Sine
Waveform
time_series
time_series
Forecaster
HoltWinters
SNARIMAX
evaluate
tree
tree
ExtremelyFastDecisionTreeClassifier
HoeffdingAdaptiveTreeClassifier
HoeffdingAdaptiveTreeRegressor
HoeffdingTreeClassifier
HoeffdingTreeRegressor
LabelCombinationHoeffdingTreeClassifier
SGTClassifier
SGTRegressor
iSOUPTreeRegressor
splitter
splitter
DynamicQuantizer
EBSTSplitter
ExhaustiveSplitter
GaussianSplitter
HistogramSplitter
QOSplitter
Quantizer
Splitter
StaticQuantizer
TEBSTSplitter
utils
utils
Histogram
SDFT
Skyline
SortedWindow
VectorDict
Window
check_estimator
dict2numpy
expand_param_grid
log_method_calls
numpy2dict
poisson
pure_inference_mode
warm_up_mode
math
math
argmax
argmax
Table of contents
Parameters
chain_dot
clamp
dot
dotvecmat
matmul2d
minkowski_distance
norm
outer
prod
sherman_morrison
sigmoid
sign
softmax
pretty
pretty
humanize_bytes
print_table
Examples
Examples
From batch to online/stream
Bike-sharing forecasting
Building a simple nowcasting model
Concept Drift
Debugging a pipeline
Working with imbalanced data
Matrix Factorization for Recommender Systems - Part 1
Matrix Factorization for Recommender Systems - Part 2
Matrix Factorization for Recommender Systems - Part 3
Handling uncertainty with quantile regression
The art of using pipelines
FAQ
FAQ
Frequently Asked Questions
Releases
Releases
Unreleased
0.9.0 - 2021-11-30
0.8.0 - 2021-08-31
0.7.2
0.7.1 - 2021-06-13
0.7.0 - 2021-04-16
0.6.1 - 2020-06-10
0.6.0 - 2020-06-09
0.5.1 - 2020-03-29
0.5.0 - 2020-03-13
0.4.4 - 2019-11-11
0.4.3 - 2019-10-27
0.4.1 - 2019-10-23
0.3.0 - 2019-06-23
0.2.0 - 2019-05-27
0.1.0 - 2019-05-08
0.0.3 - 2019-03-21
0.0.2 - 2019-02-13
Table of contents
Parameters
argmax
¶
Argmax function.
Parameters
¶
lst
(
list
)