class sklearn.preprocessing.MaxAbsScaler(copy=True)

class sklearn.model_selection.LeavePOut(p)

class sklearn.mixture.BayesianGaussianMixture(n_components=1, covariance_type='full', tol=0.001, reg_covar=1e-06, max_iter=100

class sklearn.linear_model.Lars(fit_intercept=True, verbose=False, normalize=True, precompute='auto', n_nonzero_coefs=500, eps=2.2204460492503131e-16

class sklearn.feature_selection.GenericUnivariateSelect(score_func=, mode='percentile', param=1e-05)

sklearn.feature_extraction.image.grid_to_graph(n_x, n_y, n_z=1, mask=None, return_as=, dtype=)

class sklearn.linear_model.MultiTaskLassoCV(eps=0.001, n_alphas=100, alphas=None, fit_intercept=True, normalize=False, max_iter=1000

class sklearn.cross_decomposition.PLSSVD(n_components=2, scale=True, copy=True)

class sklearn.base.TransformerMixin

sklearn.datasets.load_linnerud(return_X_y=False)