class sklearn.preprocessing.MultiLabelBinarizer(classes=None, sparse_output=False)

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

class sklearn.preprocessing.LabelEncoder

sklearn.preprocessing.scale(X, axis=0, with_mean=True, with_std=True, copy=True)

class sklearn.preprocessing.PolynomialFeatures(degree=2, interaction_only=False, include_bias=True)

sklearn.preprocessing.normalize(X, norm='l2', axis=1, copy=True, return_norm=False)

class sklearn.preprocessing.FunctionTransformer(func=None, inverse_func=None, validate=True, accept_sparse=False, pass_y=False

sklearn.preprocessing.robust_scale(X, axis=0, with_centering=True, with_scaling=True, quantile_range=(25.0, 75.0), copy=True)

sklearn.preprocessing.binarize(X, threshold=0.0, copy=True)

class sklearn.preprocessing.LabelBinarizer(neg_label=0, pos_label=1, sparse_output=False)