content: """
  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 label_ranking_average_precision_score
  from .ranking import label_ranking_loss
  from .ranking import precision_recall_curve
  from .ranking import roc_auc_score
  from .ranking import roc_curve
  from .ranking import dcg_score
  from .ranking import ndcg_score
  
  from .classification import accuracy_score
  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_similarity_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 . import cluster
  from .cluster import adjusted_mutual_info_score
  from .cluster import adjusted_rand_score
  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_harabaz_score
  from .cluster import v_measure_score
  
  from .pairwise import 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 .regression import explained_variance_score
  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 r2_score
  
  from .scorer import make_scorer
  from .scorer import SCORERS
  from .scorer import get_scorer
  
  __all__ = [
      'accuracy_score',
      'adjusted_mutual_info_score',
      'adjusted_rand_score',
      'auc',
      'average_precision_score',
      'classification_report',
      'cluster',
      'completeness_score',
      'confusion_matrix',
      'consensus_score',
      'coverage_error',
      'euclidean_distances',
      'explained_variance_score',
      'f1_score',
      'fbeta_score',
      'get_scorer',
      'hamming_loss',
      'hinge_loss',
      'homogeneity_completeness_v_measure',
      'homogeneity_score',
      'jaccard_similarity_score',
      'label_ranking_average_precision_score',
      'label_ranking_loss',
      'log_loss',
      'make_scorer',
      'matthews_corrcoef',
      'mean_absolute_error',
      'mean_squared_error',
      'mean_squared_log_error',
      'median_absolute_error',
      'mutual_info_score',
      'normalized_mutual_info_score',
      'pairwise_distances',
      'pairwise_distances_argmin',
      'pairwise_distances_argmin_min',
      'pairwise_distances_argmin_min',
      'pairwise_kernels',
      'precision_recall_curve',
      'precision_recall_fscore_support',
      'precision_score',
      'r2_score',
      'recall_score',
      'roc_auc_score',
      'roc_curve',
      'SCORERS',
      'silhouette_samples',
      'silhouette_score',
      'v_measure_score',
      'zero_one_loss',
      'brier_score_loss',
      'dcg_score',
      'ndcg_score'
  ]
  