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"""
The :mod:`sklearn.metrics` module includes score functions, performance metrics
and pairwise metrics and distance computations.
"""
from ._ranking import auc
from ._ranking import average_precision_score
from ._ranking import coverage_error
from ._ranking import det_curve
from ._ranking import dcg_score
from ._ranking import label_ranking_average_precision_score
from ._ranking import label_ranking_loss
from ._ranking import ndcg_score
from ._ranking import precision_recall_curve
from ._ranking import roc_auc_score
from ._ranking import roc_curve
from ._ranking import top_k_accuracy_score
from ._classification import accuracy_score
from ._classification import balanced_accuracy_score
from ._classification import class_likelihood_ratios
from ._classification import classification_report
from ._classification import cohen_kappa_score
from ._classification import confusion_matrix
from ._classification import f1_score
from ._classification import fbeta_score
from ._classification import hamming_loss
from ._classification import hinge_loss
from ._classification import jaccard_score
from ._classification import log_loss
from ._classification import matthews_corrcoef
from ._classification import precision_recall_fscore_support
from ._classification import precision_score
from ._classification import recall_score
from ._classification import zero_one_loss
from ._classification import brier_score_loss
from ._classification import multilabel_confusion_matrix
from ._dist_metrics import DistanceMetric
from . import cluster
from .cluster import adjusted_mutual_info_score
from .cluster import adjusted_rand_score
from .cluster import rand_score
from .cluster import pair_confusion_matrix
from .cluster import completeness_score
from .cluster import consensus_score
from .cluster import homogeneity_completeness_v_measure
from .cluster import homogeneity_score
from .cluster import mutual_info_score
from .cluster import normalized_mutual_info_score
from .cluster import fowlkes_mallows_score
from .cluster import silhouette_samples
from .cluster import silhouette_score
from .cluster import calinski_harabasz_score
from .cluster import v_measure_score
from .cluster import davies_bouldin_score
from .pairwise import euclidean_distances
from .pairwise import nan_euclidean_distances
from .pairwise import pairwise_distances
from .pairwise import pairwise_distances_argmin
from .pairwise import pairwise_distances_argmin_min
from .pairwise import pairwise_kernels
from .pairwise import pairwise_distances_chunked
from ._regression import explained_variance_score
from ._regression import max_error
from ._regression import mean_absolute_error
from ._regression import mean_squared_error
from ._regression import mean_squared_log_error
from ._regression import median_absolute_error
from ._regression import mean_absolute_percentage_error
from ._regression import mean_pinball_loss
from ._regression import r2_score
from ._regression import mean_tweedie_deviance
from ._regression import mean_poisson_deviance
from ._regression import mean_gamma_deviance
from ._regression import d2_tweedie_score
from ._regression import d2_pinball_score
from ._regression import d2_absolute_error_score
from ._scorer import check_scoring
from ._scorer import make_scorer
from ._scorer import SCORERS
from ._scorer import get_scorer
from ._scorer import get_scorer_names
from ._plot.det_curve import DetCurveDisplay
from ._plot.roc_curve import RocCurveDisplay
from ._plot.precision_recall_curve import PrecisionRecallDisplay
from ._plot.confusion_matrix import ConfusionMatrixDisplay
from ._plot.regression import PredictionErrorDisplay
__all__ = [
"accuracy_score",
"adjusted_mutual_info_score",
"adjusted_rand_score",
"auc",
"average_precision_score",
"balanced_accuracy_score",
"calinski_harabasz_score",
"check_scoring",
"class_likelihood_ratios",
"classification_report",
"cluster",
"cohen_kappa_score",
"completeness_score",
"ConfusionMatrixDisplay",
"confusion_matrix",
"consensus_score",
"coverage_error",
"d2_tweedie_score",
"d2_absolute_error_score",
"d2_pinball_score",
"dcg_score",
"davies_bouldin_score",
"DetCurveDisplay",
"det_curve",
"DistanceMetric",
"euclidean_distances",
"explained_variance_score",
"f1_score",
"fbeta_score",
"fowlkes_mallows_score",
"get_scorer",
"hamming_loss",
"hinge_loss",
"homogeneity_completeness_v_measure",
"homogeneity_score",
"jaccard_score",
"label_ranking_average_precision_score",
"label_ranking_loss",
"log_loss",
"make_scorer",
"nan_euclidean_distances",
"matthews_corrcoef",
"max_error",
"mean_absolute_error",
"mean_squared_error",
"mean_squared_log_error",
"mean_pinball_loss",
"mean_poisson_deviance",
"mean_gamma_deviance",
"mean_tweedie_deviance",
"median_absolute_error",
"mean_absolute_percentage_error",
"multilabel_confusion_matrix",
"mutual_info_score",
"ndcg_score",
"normalized_mutual_info_score",
"pair_confusion_matrix",
"pairwise_distances",
"pairwise_distances_argmin",
"pairwise_distances_argmin_min",
"pairwise_distances_chunked",
"pairwise_kernels",
"PrecisionRecallDisplay",
"precision_recall_curve",
"precision_recall_fscore_support",
"precision_score",
"PredictionErrorDisplay",
"r2_score",
"rand_score",
"recall_score",
"RocCurveDisplay",
"roc_auc_score",
"roc_curve",
"SCORERS",
"get_scorer_names",
"silhouette_samples",
"silhouette_score",
"top_k_accuracy_score",
"v_measure_score",
"zero_one_loss",
"brier_score_loss",
]
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