sklearn.covariance.graph_lasso(emp_cov, alpha, cov_init=None, mode='cd', tol=0.0001, enet_tol=0.0001, max_iter=100, verbose=False

sklearn.preprocessing.label_binarize(y, classes, neg_label=0, pos_label=1, sparse_output=False)

sklearn.utils.resample(*arrays, **options)

sklearn.datasets.make_sparse_coded_signal(n_samples, n_components, n_features, n_nonzero_coefs, random_state=None)

class sklearn.pipeline.Pipeline(steps)

class sklearn.ensemble.AdaBoostClassifier(base_estimator=None, n_estimators=50, learning_rate=1.0, algorithm='SAMME.R', random_state=None)

sklearn.metrics.label_ranking_average_precision_score(y_true, y_score)

sklearn.feature_selection.mutual_info_classif(X, y, discrete_features='auto', n_neighbors=3, copy=True, random_state=None)

sklearn.metrics.brier_score_loss(y_true, y_prob, sample_weight=None, pos_label=None)

sklearn.metrics.mean_absolute_error(y_true, y_pred, sample_weight=None, multioutput='uniform_average')