Trains Modules for PySkOptimize

class pyskoptimize.traits.HasEstimator(*, model: pyskoptimize.steps.SklearnTransformerModel)

The estimator trait

Variables

model – The sklearn transformer configurations for the model

property estimator

This generates the base estimator for the machine learning task

Returns

the base estimator

property estimator_param_space: Dict

This generates the parameter space for the Bayesian search

Returns

The search space

class pyskoptimize.traits.HasFeaturePostProcessing(*, postProcess: pyskoptimize.steps.PostProcessingFeaturePodModel)

The feature post processing trait

Variables

postprocess – The list of postprocessing steps to apply onto the feature union

property post_process_pipeline

This generates the base estimator for the machine learning task

Returns

the base estimator

property post_process_pipeline_param_space

This generates the parameter space for the Bayesian search

Returns

The search space

class pyskoptimize.traits.HasFeaturePreprocessing(*, preprocess: List[pyskoptimize.steps.PreprocessingFeaturePodModel])

The feature preprocessing trait

Variables

preprocess – The list of preprocessing applications on different features

property preprocess_pipeline

This generates the base estimator for the machine learning task

Returns

the base estimator

property preprocess_pipeline_param_space

This generates the parameter space for the Bayesian search

Returns

The search space

class pyskoptimize.traits.IsMLPipeline

The base ML Pipeline to standardize which properties to expect