Multi-label feature selection using q-rung orthopair hesitant fuzzy MCDM approach extended to CODAS

Abstract

This work addresses the issue of multi-label feature selection by extending the CODAS technique with a q-rung orthopair hesitant fuzzy multi-criteria decision-making approach. The methodology of proposing CODAS methodology in the q-rung orthopair hesitant fuzzy set environment and utilizing it in a multi-label feature selection problem is the first and only such extension of the CODAS algorithm in the literature. To generate a decision matrix, the proposed method MFS q-ROHFS MCDM views the technique as an information fusion process. Experimental results are compared to other ways using the same performance criteria to exhibit the efficacy and superiority of the suggested approach.