sklearn.metrics.matthews_corrcoef(y_true, y_pred, sample_weight=None)

sklearn.metrics.homogeneity_score(labels_true, labels_pred)

sklearn.metrics.calinski_harabaz_score(X, labels)

sklearn.metrics.pairwise.paired_euclidean_distances(X, Y)

sklearn.metrics.pairwise.sigmoid_kernel(X, Y=None, gamma=None, coef0=1)

sklearn.metrics.pairwise.kernel_metrics()

sklearn.metrics.label_ranking_average_precision_score(y_true, y_score)

sklearn.metrics.make_scorer(score_func, greater_is_better=True, needs_proba=False, needs_threshold=False, **kwargs)

sklearn.metrics.silhouette_samples(X, labels, metric='euclidean', **kwds)

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