sklearn.metrics.pairwise.cosine_distances(X, Y=None)

class sklearn.svm.LinearSVC(penalty='l2', loss='squared_hinge', dual=True, tol=0.0001, C=1.0, multi_class='ovr', fit_intercept=True, intercept_scaling=1

class sklearn.cross_decomposition.PLSCanonical(n_components=2, scale=True, algorithm='nipals', max_iter=500, tol=1e-06, copy=True)

sklearn.metrics.precision_recall_curve(y_true, probas_pred, pos_label=None, sample_weight=None)

sklearn.datasets.make_hastie_10_2(n_samples=12000, random_state=None)

sklearn.metrics.pairwise.cosine_similarity(X, Y=None, dense_output=True)

class sklearn.feature_extraction.text.HashingVectorizer(input=u'content', encoding=u'utf-8', decode_error=u'strict'

class sklearn.feature_extraction.FeatureHasher(n_features=1048576, input_type='dict', dtype=, non_negative=False)

sklearn.metrics.average_precision_score(y_true, y_score, average='macro', sample_weight=None)

sklearn.datasets.load_breast_cancer(return_X_y=False)