Framework for Explainability with Recourse of Black-Box Trained Classifiers and Assessment of Fairness and Robustness of Black-Box Trained Classifiers (2019)
A method, system and computer-readable storage medium for performing a counterfactual generation operation. The counterfactual generation operation includes: receiving a subject data point; classifying the data point via a trained classifier, the classifying providing a classified data point; identifying a counterfactual using the classified data point, the counterfactual comprising another datapoint, the another data point being close to the subject data point, the another data point resulting in production of a different outcome when provided to a model when compared to an outcome resulting from the subject data point being provided to the model; and, providing the counterfactual to a destination.