Self-adaptive weighted interaction feature selection based on robust fuzzy dominance rough sets for monotonic classification

precision fuzzy dominance neighborhood rough set (PFDNRS) with robustness is proposed. Second, a feature evaluation index is presented, which not only considers the correlation between features and decision, but also considers the interaction between features. Finally, a SWIFS) algorithm is designed to select a feature sequence. Extensive experiments are conducted on fifteen public datasets, and the results show that the