sklearn

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

@anandabastakoti/sum-of-digits

This is the firs npm package I developed in which the function takes an positive integer and returns the sum of all the digits