simpleml.pipelines.sklearn.external_pipeline

External pipeline support for scikit-learn pipeline

Module Contents

Classes

SklearnExternalPipeline

wrap sklearn pipeline with standardized methods

Attributes

__author__

simpleml.pipelines.sklearn.external_pipeline.__author__ = Elisha Yadgaran

class simpleml.pipelines.sklearn.external_pipeline.SklearnExternalPipeline(steps, *, memory=None, verbose=False)

Bases: sklearn.pipeline.Pipeline, simpleml.pipelines.external_pipelines.ExternalPipelineMixin

wrap sklearn pipeline with standardized methods

add_transformer(self, name, transformer, index=None)

Setter method for new transformer step

Parameters

• name (str) –

• transformer (Any) –

• index (Optional[int]) –

Return type

None

get_feature_names(self, feature_names)

Iterate through each transformer and return list of resulting features starts with empty list by default but can pass in dataset as starting point to guide transformations

Parameters

feature_names (List[str]) – list of initial feature names before transformations

Type

list

Return type

List[str]

get_params(self, params_only=False, **kwargs)

Wrapper around sklearn implementation to drop non parameter returns :param params_only: boolean to filter down to actual transformer parameters

Parameters

params_only (Optional[bool]) –

Return type

Dict[str, Any]

get_transformers(self)

Get list of (step, transformer) tuples

Return type

List[Tuple[str, str]]

remove_transformer(self, name)

Delete method for transformer step

Parameters

name (str) –

Return type

None