sklearn

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

shard-loads-equalizer

This package ensures Playwright test shards are evenly distributed based on execution time, so each shard finishes in roughly the same duration. It optimizes resource utilization and minimizes total test run time by balancing the load across all shards.