159 lines
4.9 KiB
Python
159 lines
4.9 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 dcg_score
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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 ndcg_score
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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 balanced_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_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 ._classification import multilabel_confusion_matrix
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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_harabasz_score
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from .cluster import v_measure_score
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from .cluster import davies_bouldin_score
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from .pairwise import euclidean_distances
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from .pairwise import nan_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 .pairwise import pairwise_distances_chunked
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from ._regression import explained_variance_score
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from ._regression import max_error
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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 ._regression import mean_tweedie_deviance
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from ._regression import mean_poisson_deviance
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from ._regression import mean_gamma_deviance
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from ._scorer import check_scoring
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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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from ._plot.roc_curve import plot_roc_curve
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from ._plot.roc_curve import RocCurveDisplay
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from ._plot.precision_recall_curve import plot_precision_recall_curve
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from ._plot.precision_recall_curve import PrecisionRecallDisplay
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from ._plot.confusion_matrix import plot_confusion_matrix
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from ._plot.confusion_matrix import ConfusionMatrixDisplay
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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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'balanced_accuracy_score',
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'calinski_harabasz_score',
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'check_scoring',
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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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'ConfusionMatrixDisplay',
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'confusion_matrix',
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'consensus_score',
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'coverage_error',
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'dcg_score',
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'davies_bouldin_score',
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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_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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'nan_euclidean_distances',
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'matthews_corrcoef',
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'max_error',
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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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'mean_poisson_deviance',
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'mean_gamma_deviance',
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'mean_tweedie_deviance',
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'median_absolute_error',
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'multilabel_confusion_matrix',
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'mutual_info_score',
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'ndcg_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_chunked',
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'pairwise_kernels',
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'plot_confusion_matrix',
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'plot_precision_recall_curve',
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'plot_roc_curve',
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'PrecisionRecallDisplay',
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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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'RocCurveDisplay',
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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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