class sklearn.preprocessing.RobustScaler(with_centering=True, with_scaling=True, quantile_range=(25.0, 75.0), copy=True)

sklearn.linear_model.lasso_stability_path(X, y, scaling=0.5, random_state=None, n_resampling=200, n_grid=100, sample_fraction=0

class sklearn.cluster.SpectralClustering(n_clusters=8, eigen_solver=None, random_state=None, n_init=10, gamma=1.0, affinity='rbf'

sklearn.datasets.make_checkerboard(shape, n_clusters, noise=0.0, minval=10, maxval=100, shuffle=True, random_state=None)

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

class sklearn.multioutput.MultiOutputClassifier(estimator, n_jobs=1)

class sklearn.linear_model.ARDRegression(n_iter=300, tol=0.001, alpha_1=1e-06, alpha_2=1e-06, lambda_1=1e-06, lambda_2=1e-06, compute_score=False

class sklearn.ensemble.RandomTreesEmbedding(n_estimators=10, max_depth=5, min_samples_split=2, min_samples_leaf=1, min_weight_fraction_leaf=0

class sklearn.linear_model.LassoLars(alpha=1.0, fit_intercept=True, verbose=False, normalize=True, precompute='auto', max_iter=500,

sklearn.linear_model.orthogonal_mp(X, y, n_nonzero_coefs=None, tol=None, precompute=False, copy_X=True, return_path=False, r