sklearn.preprocessing (original) (raw)

Methods for scaling, centering, normalization, binarization, and more.

Binarizer	Binarize data (set feature values to 0 or 1) according to a threshold.
FunctionTransformer	Constructs a transformer from an arbitrary callable.
KBinsDiscretizer	Bin continuous data into intervals.
KernelCenterer	Center an arbitrary kernel matrix \(K\).
LabelBinarizer	Binarize labels in a one-vs-all fashion.
LabelEncoder	Encode target labels with value between 0 and n_classes-1.
MaxAbsScaler	Scale each feature by its maximum absolute value.
MinMaxScaler	Transform features by scaling each feature to a given range.
MultiLabelBinarizer	Transform between iterable of iterables and a multilabel format.
Normalizer	Normalize samples individually to unit norm.
OneHotEncoder	Encode categorical features as a one-hot numeric array.
OrdinalEncoder	Encode categorical features as an integer array.
PolynomialFeatures	Generate polynomial and interaction features.
PowerTransformer	Apply a power transform featurewise to make data more Gaussian-like.
QuantileTransformer	Transform features using quantiles information.
RobustScaler	Scale features using statistics that are robust to outliers.
SplineTransformer	Generate univariate B-spline bases for features.
StandardScaler	Standardize features by removing the mean and scaling to unit variance.
TargetEncoder	Target Encoder for regression and classification targets.
add_dummy_feature	Augment dataset with an additional dummy feature.
binarize	Boolean thresholding of array-like or scipy.sparse matrix.
label_binarize	Binarize labels in a one-vs-all fashion.
maxabs_scale	Scale each feature to the [-1, 1] range without breaking the sparsity.
minmax_scale	Transform features by scaling each feature to a given range.
normalize	Scale input vectors individually to unit norm (vector length).
power_transform	Parametric, monotonic transformation to make data more Gaussian-like.
quantile_transform	Transform features using quantiles information.
robust_scale	Standardize a dataset along any axis.
scale	Standardize a dataset along any axis.