Third Order Backward Elimination Approach for Fuzzy-Rough Set Based Feature Selection

Abstract

Two important control strategies for Rough Set based reduct computation are Sequential Forward Selection (SFS), and Sequential Backward Elimination (SBE). SBE methods have an inherent advantage of resulting in reduct whereas SFS approaches usually result in superset of reduct. The fuzzy rough sets is an extension of rough sets used for reduct computation in Hybrid Decision Systems. The SBE based fuzzy rough reduct computation has not attempted till date by researchers due to the fuzzy similarity relation of a set of attributes will not typically lead to fuzzy similarity relation of the subset of attributes. This paper proposes a novel SBE approach based on Gaussian Kernel-based fuzzy rough set reduct computation. The complexity of the proposed approach is the order of three while existing are fourth order. Empirical experiment conducted on standard benchmark datasets established the relevance of the proposed approach.