pyreal.transformers.DataFrameWrapper

class pyreal.transformers.DataFrameWrapper(wrapped_transformer, **kwargs)

Allows use of standard sklearn transformers while maintaining DataFrame type. Same functionality as Transformer (kept for backwards compatibility).

__init__(wrapped_transformer, **kwargs)

Initialize the wrapped transformer

Parameters:

wrapped_transformer –

Methods

__init__(wrapped_transformer, **kwargs)	Initialize the wrapped transformer
data_transform(x)	Transform x using the wrapped transformer :param x: The dataset to transform :type x: DataFrame of shape (n_instances, n_features)
fit(x, **params)	Fit the wrapped transformer
fit_transform(x, **fit_params)	Fits this transformer to data and then transforms the same data
inverse_data_transform(x_new)	Inverse transform x_new using the wrapped transformer :param x_new: The dataset to inverse transform :type x_new: DataFrame of shape (n_instances, n_transformed_features)
inverse_transform(x_new)	Transforms data x_new from new feature space back into the original feature space.
inverse_transform_explanation(explanation)	Transforms the explanation from the second feature space handled by this transformer to the first.
inverse_transform_explanation_additive_feature_contribution(...)	Inverse transforms additive feature contribution explanations
inverse_transform_explanation_additive_feature_importance(...)	Inverse transforms additive feature importance explanations
inverse_transform_explanation_decision_tree(...)	Inverse transforms decision-tree explanations
inverse_transform_explanation_example(...)	Inverse transforms example-based explanations
inverse_transform_explanation_feature_based(...)	Inverse transforms feature-based explanations
inverse_transform_explanation_feature_contribution(...)	Inverse transforms feature contribution explanations
inverse_transform_explanation_feature_importance(...)	Inverse transforms feature importance explanations
inverse_transform_explanation_similar_example(...)	Inverse transforms similar-example-based explanations
set_flags([model, interpret, algorithm])
transform(x)	Wrapper for data_transform.
transform_explanation(explanation)	Transforms the explanation from the first feature space handled by this transformer to the second.
transform_explanation_additive_feature_contribution(...)	Transforms additive feature contribution explanations
transform_explanation_additive_feature_importance(...)	Transforms additive feature importance explanations
transform_explanation_decision_tree(explanation)	Inverse transforms feature-based explanations
transform_explanation_example(explanation)	Transforms example-based explanations
transform_explanation_feature_based(explanation)	Transforms feature-based explanations
transform_explanation_feature_contribution(...)	Transforms feature contribution explanations
transform_explanation_feature_importance(...)	Transforms feature importance explanations
transform_explanation_similar_example(...)	Transforms example-based explanations