simpleml.pipelines.sklearn.base

Base Sklearn pipeline wrapper

Module Contents

Classes

SklearnPipeline

Scikit-Learn Pipeline implementation

Attributes

LOGGER

__author__

simpleml.pipelines.sklearn.base.LOGGER[source]
simpleml.pipelines.sklearn.base.__author__ = Elisha Yadgaran[source]
class simpleml.pipelines.sklearn.base.SklearnPipeline(has_external_files=True, transformers=None, fitted=False, dataset_id=None, **kwargs)[source]

Bases: simpleml.pipelines.base_pipeline.Pipeline

Scikit-Learn Pipeline implementation

Parameters

  • has_external_files (bool) –

  • transformers (Optional[List[Any]]) –

  • fitted (bool) –

  • dataset_id (Optional[Union[str, uuid.uuid4]]) –

_create_external_pipeline(self, transformers, **kwargs)[source]

Initialize a scikit-learn pipeline object

Parameters

transformers (List[Any]) –

Return type

simpleml.pipelines.sklearn.external_pipeline.SklearnExternalPipeline

_filter_fit_params(self, split)[source]

Sklearn Pipelines register arbitrary input kwargs but validate non X,y as stepname__parameter format

Parameters

split (simpleml.pipelines.projected_splits.ProjectedDatasetSplit) –

Return type

Dict[str, Any]