class sklearn.decomposition.MiniBatchSparsePCA(n_components=None, alpha=1, ridge_alpha=0.01, n_iter=100, callback=None, batch_size=3

class sklearn.linear_model.TheilSenRegressor(fit_intercept=True, copy_X=True, max_subpopulation=10000.0, n_subsamples=None,

class sklearn.neighbors.NearestCentroid(metric='euclidean', shrink_threshold=None)

sklearn.datasets.fetch_lfw_people(data_home=None, funneled=True, resize=0.5, min_faces_per_person=0, color=False, slice_=(slice(70

class sklearn.preprocessing.StandardScaler(copy=True, with_mean=True, with_std=True)

class sklearn.feature_extraction.text.TfidfTransformer(norm=u'l2', use_idf=True, smooth_idf=True, sublinear_tf=False)

class sklearn.kernel_approximation.Nystroem(kernel='rbf', gamma=None, coef0=1, degree=3, kernel_params=None, n_components=100

class sklearn.decomposition.PCA(n_components=None, copy=True, whiten=False, svd_solver='auto', tol=0.0, iterated_power='auto', random_state=None)

class sklearn.gaussian_process.kernels.Matern(length_scale=1.0, length_scale_bounds=(1e-05, 100000.0), nu=1.5)

sklearn.metrics.hamming_loss(y_true, y_pred, labels=None, sample_weight=None, classes=None)