sklearn.model_selection.cross_val_score(estimator, X, y=None, groups=None, scoring=None, cv=None, n_jobs=1, verbose=0, fit_params=None

class sklearn.neighbors.NearestNeighbors(n_neighbors=5, radius=1.0, algorithm='auto', leaf_size=30, metric='minkowski', p=2, metric_params=None

class sklearn.model_selection.LeavePGroupsOut(n_groups)

class sklearn.feature_selection.SelectFwe(score_func=, alpha=0.05)

sklearn.datasets.fetch_20newsgroups(data_home=None, subset='train', categories=None, shuffle=True, random_state=42, remove=()

class sklearn.model_selection.ShuffleSplit(n_splits=10, test_size=0.1, train_size=None, random_state=None)

class sklearn.preprocessing.OneHotEncoder(n_values='auto', categorical_features='all', dtype=, sparse=True, handle_unknown='error')

sklearn.isotonic.check_increasing(x, y)

class sklearn.semi_supervised.LabelSpreading(kernel='rbf', gamma=20, n_neighbors=7, alpha=0.2, max_iter=30, tol=0.001, n_jobs=1)