Generating Sparse and Valid Counterfactual Explanations for Time-Series Classification using Multi-Objective Evolutionary Optimization

TX-Gen, a novel algorithm based on evolutionary multi-objective optimization, generates a diverse set of sparse and valid counterfactual explanations for time-series classification models while maintaining proximity to the original input.