Preprocessor#

Preprocessor Interface#

Constructor#

Preprocessor

Implements an ML preprocessing operation.

Fit/Transform APIs#

fit

Fit this Preprocessor to the Dataset.

fit_transform

Fit this Preprocessor to the Dataset and then transform the Dataset.

transform

Transform the given dataset.

transform_batch

Transform a single batch of data.

PreprocessorNotFittedException

Error raised when the preprocessor needs to be fitted first.

Generic Preprocessors#

Concatenator

Combine numeric columns into a column of type TensorDtype.

SimpleImputer

Replace missing values with imputed values.

Categorical Encoders#

Categorizer

Convert columns to pd.CategoricalDtype.

LabelEncoder

Encode labels as integer targets.

MultiHotEncoder

Multi-hot encode categorical data.

OneHotEncoder

One-hot encode categorical data.

OrdinalEncoder

Encode values within columns as ordered integer values.

Feature Scalers#

MaxAbsScaler

Scale each column by its absolute max value.

MinMaxScaler

Scale each column by its range.

Normalizer

Scales each sample to have unit norm.

PowerTransformer

Apply a power transform to make your data more normally distributed.

RobustScaler

Scale and translate each column using quantiles.

StandardScaler

Translate and scale each column by its mean and standard deviation, respectively.

K-Bins Discretizers#

CustomKBinsDiscretizer

Bin values into discrete intervals using custom bin edges.

UniformKBinsDiscretizer

Bin values into discrete intervals (bins) of uniform width.