ml_preprocessing library
Classes
- Encoder
- Categorical data encoder factory
- Normalizer
- Pipeline
- A class, that is used to organize data preprocessing stages in a pipeline manner.
- Standardizer
- A class that performs data standardization.
Enums
- Norm
- Vector norm types
- UnknownValueHandlingType
Constants
Functions
-
encodeAsIntegerLabels(
{Iterable< int> ? features, Iterable<String> ? featureNames, String headerPrefix = '', String headerPostfix = '', UnknownValueHandlingType unknownValueHandlingType = defaultUnknownValueHandlingType}) → PipeableOperatorFn - A factory function to use label categorical data encoder in pipeline
-
encodeAsOneHotLabels(
{Iterable< int> ? features, Iterable<String> ? featureNames, String headerPrefix = '', String headerPostfix = '', UnknownValueHandlingType unknownValueHandlingType = defaultUnknownValueHandlingType}) → PipeableOperatorFn -
A factory function to use
one hotcategorical data encoder in pipeline -
normalize(
[Norm norm = Norm.euclidean]) → PipeableOperatorFn -
standardize(
) → PipeableOperatorFn