120 lines
3.6 KiB
Python
120 lines
3.6 KiB
Python
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"""
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The :mod:`sklearn.metrics` module includes score functions, performance metrics
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and pairwise metrics and distance computations.
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"""
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from .ranking import auc
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from .ranking import average_precision_score
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from .ranking import coverage_error
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from .ranking import label_ranking_average_precision_score
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from .ranking import label_ranking_loss
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from .ranking import precision_recall_curve
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from .ranking import roc_auc_score
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from .ranking import roc_curve
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from .classification import accuracy_score
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from .classification import classification_report
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from .classification import cohen_kappa_score
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from .classification import confusion_matrix
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from .classification import f1_score
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from .classification import fbeta_score
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from .classification import hamming_loss
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from .classification import hinge_loss
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from .classification import jaccard_similarity_score
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from .classification import log_loss
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from .classification import matthews_corrcoef
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from .classification import precision_recall_fscore_support
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from .classification import precision_score
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from .classification import recall_score
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from .classification import zero_one_loss
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from .classification import brier_score_loss
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from . import cluster
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from .cluster import adjusted_mutual_info_score
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from .cluster import adjusted_rand_score
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from .cluster import completeness_score
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from .cluster import consensus_score
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from .cluster import homogeneity_completeness_v_measure
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from .cluster import homogeneity_score
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from .cluster import mutual_info_score
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from .cluster import normalized_mutual_info_score
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from .cluster import fowlkes_mallows_score
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from .cluster import silhouette_samples
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from .cluster import silhouette_score
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from .cluster import calinski_harabaz_score
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from .cluster import v_measure_score
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from .pairwise import euclidean_distances
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from .pairwise import pairwise_distances
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from .pairwise import pairwise_distances_argmin
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from .pairwise import pairwise_distances_argmin_min
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from .pairwise import pairwise_kernels
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from .regression import explained_variance_score
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from .regression import mean_absolute_error
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from .regression import mean_squared_error
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from .regression import mean_squared_log_error
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from .regression import median_absolute_error
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from .regression import r2_score
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from .scorer import make_scorer
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from .scorer import SCORERS
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from .scorer import get_scorer
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__all__ = [
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'accuracy_score',
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'adjusted_mutual_info_score',
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'adjusted_rand_score',
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'auc',
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'average_precision_score',
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'calinski_harabaz_score',
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'classification_report',
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'cluster',
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'cohen_kappa_score',
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'completeness_score',
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'confusion_matrix',
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'consensus_score',
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'coverage_error',
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'euclidean_distances',
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'explained_variance_score',
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'f1_score',
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'fbeta_score',
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'fowlkes_mallows_score',
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'get_scorer',
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'hamming_loss',
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'hinge_loss',
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'homogeneity_completeness_v_measure',
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'homogeneity_score',
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'jaccard_similarity_score',
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'label_ranking_average_precision_score',
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'label_ranking_loss',
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'log_loss',
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'make_scorer',
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'matthews_corrcoef',
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'mean_absolute_error',
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'mean_squared_error',
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'mean_squared_log_error',
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'median_absolute_error',
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'mutual_info_score',
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'normalized_mutual_info_score',
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'pairwise_distances',
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'pairwise_distances_argmin',
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'pairwise_distances_argmin_min',
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'pairwise_distances_argmin_min',
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'pairwise_kernels',
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'precision_recall_curve',
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'precision_recall_fscore_support',
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'precision_score',
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'r2_score',
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'recall_score',
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'roc_auc_score',
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'roc_curve',
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'SCORERS',
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'silhouette_samples',
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'silhouette_score',
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'v_measure_score',
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'zero_one_loss',
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'brier_score_loss',
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]
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