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sklearn/metrics/__init__.py
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Lucy Liu
FEA Add metric_at_thresholds (#32732)
07 мар 2026, 08:58
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07 мар 2026, 08:58
3acced3
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"""Score functions, performance metrics, pairwise metrics and distance computations.""" # Authors: The scikit-learn developers # SPDX-License-Identifier: BSD-3-Clause from sklearn.metrics import cluster from sklearn.metrics._classification import ( accuracy_score, balanced_accuracy_score, brier_score_loss, class_likelihood_ratios, classification_report, cohen_kappa_score, confusion_matrix, d2_brier_score, d2_log_loss_score, f1_score, fbeta_score, hamming_loss, hinge_loss, jaccard_score, log_loss, matthews_corrcoef, multilabel_confusion_matrix, precision_recall_fscore_support, precision_score, recall_score, zero_one_loss, ) from sklearn.metrics._dist_metrics import DistanceMetric from sklearn.metrics._plot.confusion_matrix import ConfusionMatrixDisplay from sklearn.metrics._plot.det_curve import DetCurveDisplay from sklearn.metrics._plot.precision_recall_curve import PrecisionRecallDisplay from sklearn.metrics._plot.regression import PredictionErrorDisplay from sklearn.metrics._plot.roc_curve import RocCurveDisplay from sklearn.metrics._ranking import ( auc, average_precision_score, confusion_matrix_at_thresholds, coverage_error, dcg_score, det_curve, label_ranking_average_precision_score, label_ranking_loss, metric_at_thresholds, ndcg_score, precision_recall_curve, roc_auc_score, roc_curve, top_k_accuracy_score, ) from sklearn.metrics._regression import ( d2_absolute_error_score, d2_pinball_score, d2_tweedie_score, explained_variance_score, max_error, mean_absolute_error, mean_absolute_percentage_error, mean_gamma_deviance, mean_pinball_loss, mean_poisson_deviance, mean_squared_error, mean_squared_log_error, mean_tweedie_deviance, median_absolute_error, r2_score, root_mean_squared_error, root_mean_squared_log_error, ) from sklearn.metrics._scorer import ( check_scoring, get_scorer, get_scorer_names, make_scorer, ) from sklearn.metrics.cluster import ( adjusted_mutual_info_score, adjusted_rand_score, calinski_harabasz_score, completeness_score, consensus_score, davies_bouldin_score, fowlkes_mallows_score, homogeneity_completeness_v_measure, homogeneity_score, mutual_info_score, normalized_mutual_info_score, pair_confusion_matrix, rand_score, silhouette_samples, silhouette_score, v_measure_score, ) from sklearn.metrics.pairwise import ( euclidean_distances, nan_euclidean_distances, pairwise_distances, pairwise_distances_argmin, pairwise_distances_argmin_min, pairwise_distances_chunked, pairwise_kernels, ) __all__ = [ "ConfusionMatrixDisplay", "DetCurveDisplay", "DistanceMetric", "PrecisionRecallDisplay", "PredictionErrorDisplay", "RocCurveDisplay", "accuracy_score", "adjusted_mutual_info_score", "adjusted_rand_score", "auc", "average_precision_score", "balanced_accuracy_score", "brier_score_loss", "calinski_harabasz_score", "check_scoring", "class_likelihood_ratios", "classification_report", "cluster", "cohen_kappa_score", "completeness_score", "confusion_matrix", "confusion_matrix_at_thresholds", "consensus_score", "coverage_error", "d2_absolute_error_score", "d2_brier_score", "d2_log_loss_score", "d2_pinball_score", "d2_tweedie_score", "davies_bouldin_score", "dcg_score", "det_curve", "euclidean_distances", "explained_variance_score", "f1_score", "fbeta_score", "fowlkes_mallows_score", "get_scorer", "get_scorer_names", "hamming_loss", "hinge_loss", "homogeneity_completeness_v_measure", "homogeneity_score", "jaccard_score", "label_ranking_average_precision_score", "label_ranking_loss", "log_loss", "make_scorer", "matthews_corrcoef", "max_error", "mean_absolute_error", "mean_absolute_percentage_error", "mean_gamma_deviance", "mean_pinball_loss", "mean_poisson_deviance", "mean_squared_error", "mean_squared_log_error", "mean_tweedie_deviance", "median_absolute_error", "metric_at_thresholds", "multilabel_confusion_matrix", "mutual_info_score", "nan_euclidean_distances", "ndcg_score", "normalized_mutual_info_score", "pair_confusion_matrix", "pairwise_distances", "pairwise_distances_argmin", "pairwise_distances_argmin_min", "pairwise_distances_chunked", "pairwise_kernels", "precision_recall_curve", "precision_recall_fscore_support", "precision_score", "r2_score", "rand_score", "recall_score", "roc_auc_score", "roc_curve", "root_mean_squared_error", "root_mean_squared_log_error", "silhouette_samples", "silhouette_score", "top_k_accuracy_score", "v_measure_score", "zero_one_loss", ]