GradCFA: A Hybrid Gradient-Based Counterfactual and Feature Attribution Explanation Algorithm for Local Interpretation of Neural Networks

Researchers introduce GradCFA, a new hybrid AI explanation framework that combines counterfactual explanations and feature attribution to improve transparency in neural network decisions. The algorithm extends beyond binary classification to multi-class scenarios and demonstrates superior performance in generating feasible, plausible, and diverse explanations compared to existing methods.