pyreal.transformers.Normalizer#

class pyreal.transformers.Normalizer(norm='l2', **kwargs)[source]#

Normalizes numeric features using the l1, l2, or max norm

__init__(norm='l2', **kwargs)[source]#

Initialize the transformer

Parameters:

norm (str, optional) – The norm to use to normalize each non zero sample. If norm=’max’ is used, values will be rescaled by the maximum of the absolute values. Can take values {‘l1’, ‘l2’, ‘max’}. Defaults to ‘l2’.

Methods

__init__([norm])

Initialize the transformer

data_transform(X)

Transform a dataset

fit(X[, y])

Fits a dataset to the transformer

fit_transform(X[, y])

Fits and transforms

inverse_data_transform(x_new)

Wrapper for inverse_data_transform.

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