sklearn.metrics.fowlkes_mallows_score(labels_true, labels_pred, sparse=False)

sklearn.metrics.pairwise_distances_argmin_min(X, Y, axis=1, metric='euclidean', batch_size=500, metric_kwargs=None)

sklearn.metrics.pairwise_distances(X, Y=None, metric='euclidean', n_jobs=1, **kwds)

sklearn.metrics.recall_score(y_true, y_pred, labels=None, pos_label=1, average='binary', sample_weight=None)

sklearn.metrics.zero_one_loss(y_true, y_pred, normalize=True, sample_weight=None)

sklearn.metrics.pairwise.laplacian_kernel(X, Y=None, gamma=None)

sklearn.metrics.r2_score(y_true, y_pred, sample_weight=None, multioutput=None)

sklearn.metrics.label_ranking_loss(y_true, y_score, sample_weight=None)

sklearn.metrics.roc_curve(y_true, y_score, pos_label=None, sample_weight=None, drop_intermediate=True)

sklearn.metrics.confusion_matrix(y_true, y_pred, labels=None, sample_weight=None)