wildboar.explain.counterfactual._helper#

Module Contents#

Functions#

counterfactuals(estimator, x, y, *[, train_x, ...])

Compute a single counterfactual example for each sample
wildboar.explain.counterfactual._helper.counterfactuals(estimator, x, y, *, train_x=None, train_y=None, method='best', scoring='deprecated', valid_scoring='deprecated', proximity=None, random_state=None, method_args=None)[source]#

Compute a single counterfactual example for each sample

Parameters:

  • estimator (object) – The estimator used to compute the counterfactual example

  • x (array-like of shape (n_samples, n_timestep)) – The data samples to fit counterfactuals to

  • y (array-like broadcast to shape (n_samples,)) – The desired label of the counterfactual

  • method (str or BaseCounterfactual, optional) –

    The method to generate counterfactual explanations

    • if ‘best’, infer the most appropriate counterfactual explanation method based on the estimator

      Changed in version 1.1.0.

    • if str, select counterfactual explainer from named collection. See _COUNTERFACTUALS.keys() for a list of valid values.

    • if, BaseCounterfactual use the supplied counterfactual

  • scoring (str, callable, list or dict, optional) –

    The scoring function to determine the similarity between the counterfactual sample and the original sample

    Deprecated since version 1.1: scoring was renamed to proximity in 1.1 and will be removed in 1.2.

  • proximity (str, callable, list or dict, optional) – The scoring function to determine the similarity between the counterfactual sample and the original sample

  • valid_scoring (bool, optional) –

    Only compute score for successful counterfactuals.

    Deprecated since version 1.1: valid_scoring will be removed in 1.2.

  • random_state (RandomState or int, optional) – The pseudo random number generator to ensure stable result

  • method_args (dict, optional) –

    Optional arguments to the counterfactual explainer.

    New in version 1.1.0.

Returns:

  • x_counterfactuals (ndarray of shape (n_samples, n_timestep)) – The counterfactual example.

  • valid (ndarray of shape (n_samples,)) – Indicator matrix for valid counterfactuals

  • score (ndarray of shape (n_samples,) or dict, optional) – Return score of the counterfactual transform, if scoring is not None