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aaronreidsmith / scikit-learn   python

Repository URL to install this package:

Version: 0.22 

/ preprocessing / __init__.py

"""
The :mod:`sklearn.preprocessing` module includes scaling, centering,
normalization, binarization methods.
"""

from ._function_transformer import FunctionTransformer

from ._data import Binarizer
from ._data import KernelCenterer
from ._data import MinMaxScaler
from ._data import MaxAbsScaler
from ._data import Normalizer
from ._data import RobustScaler
from ._data import StandardScaler
from ._data import QuantileTransformer
from ._data import add_dummy_feature
from ._data import binarize
from ._data import normalize
from ._data import scale
from ._data import robust_scale
from ._data import maxabs_scale
from ._data import minmax_scale
from ._data import quantile_transform
from ._data import power_transform
from ._data import PowerTransformer
from ._data import PolynomialFeatures

from ._encoders import OneHotEncoder
from ._encoders import OrdinalEncoder

from ._label import label_binarize
from ._label import LabelBinarizer
from ._label import LabelEncoder
from ._label import MultiLabelBinarizer

from ._discretization import KBinsDiscretizer


__all__ = [
    'Binarizer',
    'FunctionTransformer',
    'KBinsDiscretizer',
    'KernelCenterer',
    'LabelBinarizer',
    'LabelEncoder',
    'MultiLabelBinarizer',
    'MinMaxScaler',
    'MaxAbsScaler',
    'QuantileTransformer',
    'Normalizer',
    'OneHotEncoder',
    'OrdinalEncoder',
    'PowerTransformer',
    'RobustScaler',
    'StandardScaler',
    'add_dummy_feature',
    'PolynomialFeatures',
    'binarize',
    'normalize',
    'scale',
    'robust_scale',
    'maxabs_scale',
    'minmax_scale',
    'label_binarize',
    'quantile_transform',
    'power_transform',
]