class sklearn.decomposition.SparsePCA(n_components=None, alpha=1, ridge_alpha=0.01, max_iter=1000, tol=1e-08, method='lars', n_jobs=1

class sklearn.linear_model.RandomizedLasso(alpha='aic', scaling=0.5, sample_fraction=0.75, n_resampling=200, selection_threshold=0

class sklearn.linear_model.RANSACRegressor(base_estimator=None, min_samples=None, residual_threshold=None, is_data_valid=None

Warning DEPRECATED

sklearn.metrics.pairwise.distance_metrics()

sklearn.datasets.make_blobs(n_samples=100, n_features=2, centers=3, cluster_std=1.0, center_box=(-10.0, 10.0), shuffle=True, random_state=None)

class sklearn.gaussian_process.GaussianProcessRegressor(kernel=None, alpha=1e-10, optimizer='fmin_l_bfgs_b', n_restarts_optimizer=0

class sklearn.linear_model.LassoLarsCV(fit_intercept=True, verbose=False, max_iter=500, normalize=True, precompute='auto', cv=None

sklearn.model_selection.learning_curve(estimator, X, y, groups=None, train_sizes=array([ 0.1, 0.33, 0.55, 0.78, 1. ]), cv=None

sklearn.svm.libsvm.fit() Train the model using libsvm (low-level method)