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online-ml/river
Introduction 🍼
Recipes 🍱
Examples 🌶️
API reference
FAQ 🙋
Releases 🏗️
Benchmarks 📊
River
online-ml/river
Introduction 🍼
Introduction 🍼
Installation
Basic concepts
Getting started
Getting started
Binary classification
Multi-class classification
Regression
Why use River?
Next steps
Recipes 🍱
Recipes 🍱
Reading data
Model evaluation
Pipelines
Feature extraction
Hyperparameter tuning
Mini-batching
Incremental decision trees in river: the Hoeffding Tree case
Examples 🌶️
Examples 🌶️
From batch to online/stream
Bike-sharing forecasting
Building a simple nowcasting model
Concept Drift
Content personalization
Debugging a pipeline
Working with imbalanced data
Handling uncertainty with quantile regression
The art of using pipelines
Matrix factorization for recommender systems
Matrix factorization for recommender systems
Part 1
Part 2
Part 3
API reference
API reference
Overview
anomaly
anomaly
GaussianScorer
HalfSpaceTrees
OneClassSVM
QuantileFilter
ThresholdFilter
base
base
AnomalyDetector
base
base
Base
Classifier
Clusterer
DriftDetector
Ensemble
Estimator
MiniBatchClassifier
MiniBatchRegressor
MiniBatchTransformer
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
Prefixer
Renamer
Select
SelectType
Suffixer
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
WaterFlow
base
base
Dataset
FileDataset
RemoteDataset
SyntheticDataset
drift
drift
ADWIN
DDM
EDDM
HDDM_A
HDDM_W
KSWIN
PageHinkley
PeriodicTrigger
dummy
dummy
NoChangeClassifier
PriorClassifier
StatisticRegressor
ensemble
ensemble
ADWINBaggingClassifier
AdaBoostClassifier
AdaptiveRandomForestClassifier
AdaptiveRandomForestRegressor
BaggingClassifier
BaggingRegressor
EWARegressor
LeveragingBaggingClassifier
SRPClassifier
SRPRegressor
StackingClassifier
VotingClassifier
evaluate
evaluate
BinaryClassificationTrack
MultiClassClassificationTrack
RegressionTrack
Track
iter_progressive_val_score
progressive_val_score
facto
facto
FFMClassifier
FFMRegressor
FMClassifier
FMRegressor
FwFMClassifier
FwFMRegressor
HOFMClassifier
HOFMRegressor
feature_extraction
feature_extraction
Agg
BagOfWords
PolynomialExtender
RBFSampler
TFIDF
TargetAgg
feature_selection
feature_selection
PoissonInclusion
SelectKBest
VarianceThreshold
imblearn
imblearn
ChebyshevOverSampler
ChebyshevUnderSampler
HardSamplingClassifier
HardSamplingRegressor
RandomOverSampler
RandomSampler
RandomUnderSampler
linear_model
linear_model
ALMAClassifier
LinearRegression
LogisticRegression
PAClassifier
PARegressor
Perceptron
SoftmaxRegression
base
base
GLM
metrics
metrics
Accuracy
AdjustedMutualInfo
AdjustedRand
BalancedAccuracy
ClassificationReport
CohenKappa
Completeness
ConfusionMatrix
CrossEntropy
F1
FBeta
FowlkesMallows
GeometricMean
Homogeneity
Jaccard
LogLoss
MAE
MCC
MSE
MacroF1
MacroFBeta
MacroJaccard
MacroPrecision
MacroRecall
MicroF1
MicroFBeta
MicroJaccard
MicroPrecision
MicroRecall
MultiFBeta
MutualInfo
NormalizedMutualInfo
Precision
R2
RMSE
RMSLE
ROCAUC
Rand
Recall
Rolling
SMAPE
Silhouette
TimeRolling
VBeta
WeightedF1
WeightedFBeta
WeightedJaccard
WeightedPrecision
WeightedRecall
base
base
BinaryMetric
ClassificationMetric
Metric
Metrics
MultiClassMetric
RegressionMetric
WrapperMetric
multioutput
multioutput
ExactMatch
MacroAverage
MicroAverage
MultiLabelConfusionMatrix
PerOutput
base
base
MultiOutputClassificationMetric
MultiOutputRegressionMetric
misc
misc
CovMatrix
Histogram
SDFT
Skyline
model_selection
model_selection
EpsilonGreedyRegressor
GreedyRegressor
SuccessiveHalvingClassifier
SuccessiveHalvingRegressor
UCBRegressor
base
base
ModelSelectionClassifier
ModelSelectionRegressor
multiclass
multiclass
OneVsOneClassifier
OneVsRestClassifier
OutputCodeClassifier
multioutput
multioutput
ClassifierChain
MonteCarloClassifierChain
ProbabilisticClassifierChain
RegressorChain
naive_bayes
naive_bayes
BernoulliNB
ComplementNB
GaussianNB
MultinomialNB
neighbors
neighbors
KNNClassifier
KNNRegressor
NearestNeighbors
neural_net
neural_net
MLPRegressor
activations
activations
Identity
ReLU
Sigmoid
optim
optim
AMSGrad
AdaBound
AdaDelta
AdaGrad
AdaMax
Adam
Averager
FTRLProximal
Momentum
Nadam
NesterovMomentum
RMSProp
SGD
base
base
Initializer
Loss
Optimizer
Scheduler
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
preprocessing
preprocessing
AdaptiveStandardScaler
Binarizer
FeatureHasher
LDA
MaxAbsScaler
MinMaxScaler
Normalizer
OneHotEncoder
PredClipper
PreviousImputer
RobustScaler
StandardScaler
StatImputer
TargetStandardScaler
proba
proba
Gaussian
Multinomial
Rolling
TimeRolling
base
base
ContinuousDistribution
DiscreteDistribution
reco
reco
Baseline
BiasedMF
FunkMF
RandomNormal
base
base
Ranker
rules
rules
AMRules
stats
stats
AbsMax
AutoCorr
BayesianMean
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
Var
base
base
Bivariate
Univariate
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
ForecastingMetric
HoltWinters
HorizonMetric
SNARIMAX
evaluate
iter_evaluate
base
base
Forecaster
tree
tree
ExtremelyFastDecisionTreeClassifier
HoeffdingAdaptiveTreeClassifier
HoeffdingAdaptiveTreeRegressor
HoeffdingTreeClassifier
HoeffdingTreeRegressor
LabelCombinationHoeffdingTreeClassifier
SGTClassifier
SGTRegressor
iSOUPTreeRegressor
base
base
Branch
Leaf
splitter
splitter
DynamicQuantizer
EBSTSplitter
ExhaustiveSplitter
GaussianSplitter
HistogramSplitter
QOSplitter
Quantizer
Splitter
StaticQuantizer
TEBSTSplitter
utils
utils
SortedWindow
VectorDict
dict2numpy
expand_param_grid
log_method_calls
numpy2dict
pure_inference_mode
warm_up_mode
math
math
argmax
chain_dot
clamp
dot
dotvecmat
matmul2d
minkowski_distance
norm
outer
prod
sherman_morrison
sigmoid
sign
softmax
pretty
pretty
humanize_bytes
humanize_bytes
Table of contents
Parameters
print_table
random
random
poisson
FAQ 🙋
FAQ 🙋
Releases 🏗️
Releases 🏗️
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
0.11.1 - 2022-06-06
0.11.0 - 2022-05-28
0.10.1 - 2022-02-05
0.10.0 - 2022-02-04
0.1.0 - 2019-05-08
0.0.3 - 2019-03-21
0.0.2 - 2019-02-13
Benchmarks 📊
Benchmarks 📊
Table of contents
Parameters
humanize_bytes
¶
Returns a human-friendly byte size.
Parameters
¶
n_bytes
(
int
)