sklearn

Use Python's #1 machine learning library from Node.js
scikitlearnsklearnmachine learningmlaiSelectorMixinCalibratedClassifierCVAffinityPropagationAgglomerativeClusteringBirchDBSCANFeatureAgglomerationKMeansBisectingKMeansMiniBatchKMeansMeanShiftOPTICSSpectralClusteringSpectralBiclusteringSpectralCoclusteringColumnTransformerTransformedTargetRegressorEmpiricalCovarianceEllipticEnvelopeGraphicalLassoGraphicalLassoCVLedoitWolfMinCovDetOASShrunkCovarianceCCAPLSCanonicalPLSRegressionPLSSVDDictionaryLearningFactorAnalysisFastICAIncrementalPCAKernelPCALatentDirichletAllocationMiniBatchDictionaryLearningMiniBatchSparsePCANMFMiniBatchNMFPCASparsePCASparseCoderTruncatedSVDLinearDiscriminantAnalysisQuadraticDiscriminantAnalysisDummyClassifierDummyRegressorAdaBoostClassifierAdaBoostRegressorBaggingClassifierBaggingRegressorExtraTreesClassifierExtraTreesRegressorGradientBoostingClassifierGradientBoostingRegressorIsolationForestRandomForestClassifierRandomForestRegressorRandomTreesEmbeddingStackingClassifierStackingRegressorVotingClassifierVotingRegressorHistGradientBoostingRegressorHistGradientBoostingClassifierConvergenceWarningDataConversionWarningDataDimensionalityWarningEfficiencyWarningFitFailedWarningNotFittedErrorUndefinedMetricWarningDictVectorizerFeatureHasherPatchExtractorCountVectorizerHashingVectorizerTfidfTransformerTfidfVectorizerGenericUnivariateSelectSelectPercentileSelectKBestSelectFprSelectFdrSelectFromModelSelectFweSequentialFeatureSelectorRFERFECVVarianceThresholdGaussianProcessClassifierGaussianProcessRegressorCompoundKernelConstantKernelDotProductExpSineSquaredExponentiationHyperparameterKernelMaternPairwiseKernelProductRBFRationalQuadraticSumWhiteKernelSimpleImputerIterativeImputerMissingIndicatorKNNImputerDecisionBoundaryDisplayPartialDependenceDisplayIsotonicRegressionAdditiveChi2SamplerNystroemPolynomialCountSketchRBFSamplerSkewedChi2SamplerKernelRidgeLogisticRegressionLogisticRegressionCVPassiveAggressiveClassifierPerceptronRidgeClassifierRidgeClassifierCVSGDClassifierSGDOneClassSVMLinearRegressionRidgeRidgeCVSGDRegressorElasticNetElasticNetCVLarsLarsCVLassoLassoCVLassoLarsLassoLarsCVLassoLarsICOrthogonalMatchingPursuitOrthogonalMatchingPursuitCVARDRegressionBayesianRidgeMultiTaskElasticNetMultiTaskElasticNetCVMultiTaskLassoMultiTaskLassoCVHuberRegressorQuantileRegressorRANSACRegressorTheilSenRegressorPoissonRegressorTweedieRegressorGammaRegressorIsomapLocallyLinearEmbeddingMDSSpectralEmbeddingTSNEDistanceMetricConfusionMatrixDisplayDetCurveDisplayPrecisionRecallDisplayPredictionErrorDisplayRocCurveDisplayCalibrationDisplayBayesianGaussianMixtureGaussianMixtureGroupKFoldGroupShuffleSplitKFoldLeaveOneGroupOutLeavePGroupsOutLeaveOneOutLeavePOutPredefinedSplitRepeatedKFoldRepeatedStratifiedKFoldShuffleSplitStratifiedKFoldStratifiedShuffleSplitStratifiedGroupKFoldTimeSeriesSplitGridSearchCVHalvingGridSearchCVParameterGridParameterSamplerRandomizedSearchCVHalvingRandomSearchCVLearningCurveDisplayOneVsRestClassifierOneVsOneClassifierOutputCodeClassifierClassifierChainMultiOutputRegressorMultiOutputClassifierRegressorChainBernoulliNBCategoricalNBComplementNBGaussianNBMultinomialNBBallTreeKDTreeKernelDensityKNeighborsClassifierKNeighborsRegressorKNeighborsTransformerLocalOutlierFactorRadiusNeighborsClassifierRadiusNeighborsRegressorRadiusNeighborsTransformerNearestCentroidNearestNeighborsNeighborhoodComponentsAnalysisBernoulliRBMMLPClassifierMLPRegressorFeatureUnionPipelineBinarizerFunctionTransformerKBinsDiscretizerKernelCentererLabelBinarizerLabelEncoderMultiLabelBinarizerMaxAbsScalerMinMaxScalerNormalizerOneHotEncoderOrdinalEncoderPolynomialFeaturesPowerTransformerQuantileTransformerRobustScalerSplineTransformerStandardScalerGaussianRandomProjectionSparseRandomProjectionLabelPropagationLabelSpreadingSelfTrainingClassifierLinearSVCLinearSVRNuSVCNuSVROneClassSVMSVCSVRDecisionTreeClassifierDecisionTreeRegressorExtraTreeClassifierExtraTreeRegressorBunchParallel

minmaxscaler

Transform features by scaling each feature to a given range. References from scikit-learn