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