sklearn.datasets.make_s_curve(n_samples=100, noise=0.0, random_state=None)

class sklearn.model_selection.PredefinedSplit(test_fold)

sklearn.model_selection.validation_curve(estimator, X, y, param_name, param_range, groups=None, cv=None, scoring=None,

class sklearn.linear_model.LassoCV(eps=0.001, n_alphas=100, alphas=None, fit_intercept=True, normalize=False, precompute='auto', max_iter=1000

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.kernels.Product(k1, k2)

class sklearn.decomposition.ProjectedGradientNMF(*args, **kwargs)

sklearn.metrics.adjusted_mutual_info_score(labels_true, labels_pred)

class sklearn.covariance.EmpiricalCovariance(store_precision=True, assume_centered=False)

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