Permutation-based multi-objective evolutionary feature selection for high-dimensional data

The proposed feature selection method employs a multi-objective evolutionary algorithm to search for candidate feature subsets, with the objectives of maximizing the degradation in model performance when the selected features are shuffled, and minimizing the cardinality of the feature subset.