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204 lines
3.7 KiB
204 lines
3.7 KiB
[default]
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package=scorings
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########################################
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# scoring methods for classification
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########################################
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[accuracy_score]
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subpackage = classification
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module = Accuracy
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class = AccuracyScoring
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[precision_score]
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subpackage = classification
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module = Precision
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class = PrecisionScoring
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[recall_score]
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subpackage = classification
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module = Recall
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class = RecallScoring
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[f1_score]
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subpackage = classification
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module = F1
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class = F1Scoring
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[roc_auc_score]
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subpackage = classification
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module = ROCAUC
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class = ROCAUCScoring
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[confusion_matrix]
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subpackage = classification
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module = ConfusionMatrix
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class = ConfusionMatrixScoring
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[roc_curve]
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subpackage = classification
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module = ROCCurve
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class = ROCCurveScoring
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[precision_recall_fscore_support]
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subpackage = classification
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module = PrecisionRecallFscoreSupport
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class = PrecisionRecallFscoreSupportScoring
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###########################################
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# scoring methods for clustering
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###########################################
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[silhouette_score]
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subpackage = clustering
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module = Silhouette
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class = SilhouetteScoring
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########################################
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# scoring methods for regression
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########################################
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[r2_score]
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subpackage = regression
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module = R2
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class = R2Scoring
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[mean_squared_error]
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subpackage = regression
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module = MeanSquaredError
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class = MeanSquaredErrorScoring
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[mean_absolute_error]
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subpackage = regression
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module = MeanAbsoluteError
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class = MeanAbsoluteErrorScoring
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[explained_variance_score]
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subpackage = regression
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module = ExplainedVariance
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class = ExplainedVarianceScoring
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###########################################
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# scoring methods for statistical testing
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###########################################
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[normaltest]
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subpackage = statstest
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module = NormalTest
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class = NormalTestScoring
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[ttest_1samp]
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subpackage = statstest
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module = TTest1Samp
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class = TTestOneSampleScoring
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[f_oneway]
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subpackage = statstest
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module = FOneway
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class = FOnewayScoring
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[adfuller]
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subpackage = statstest
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module = Adfuller
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class = AdfullerScoring
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[kpss]
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subpackage = statstest
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module = KPSS
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class = KPSSScoring
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[kstest]
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subpackage = statstest
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module = KSTest
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class = KSTestScoring
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[mannwhitneyu]
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subpackage = statstest
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module = MannWhitneyU
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class = MannWhitneyUScoring
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[wilcoxon]
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subpackage = statstest
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module = Wilcoxon
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class = WilcoxonScoring
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[ttest_ind]
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subpackage = statstest
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module = TTestInd
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class = TTestTwoIndSampleScoring
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[ttest_rel]
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subpackage = statstest
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module = TTestRel
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class = TTestTwoSampleScoring
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[ks_2samp]
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subpackage = statstest
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module = KSTest2Samp
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class = KSTest2SampleScoring
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[wasserstein_distance]
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subpackage = statstest
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module = WassersteinDistance
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class = WassersteinDistanceScoring
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[energy_distance]
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subpackage = statstest
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module = EnergyDistance
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class = EnergyDistanceScoring
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[anova]
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subpackage = statstest
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module = Anova
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class = AnovaTableScoring
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#############################################
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# scoring methods for statistical functions
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#############################################
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[describe]
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subpackage = statsfunctions
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module = Describe
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class = DescribeScoring
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[moment]
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subpackage = statsfunctions
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module = Moment
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class = MomentScoring
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[tmean]
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subpackage = statsfunctions
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module = TMean
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class = TMeanScoring
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[tvar]
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subpackage = statsfunctions
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module = TVar
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class = TVarScoring
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[trim]
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subpackage = statsfunctions
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module = Trim
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class = TrimScoring
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[pearsonr]
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subpackage = statsfunctions
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module = Pearsonr
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class = PearsonrScoring
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[spearmanr]
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subpackage = statsfunctions
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module = Spearmanr
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class = SpearmanrScoring
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###########################################
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# scoring methods for pairwise distances
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###########################################
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[pairwise_distances]
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subpackage = pairwise
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module = PairwiseDistances
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class = PairwiseDistancesScoring
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