Pattern classification using grey tolerance rough sets
Yi‐Chung Hu · Kybernetes · 2016
Purpose – The purpose of this paper is to propose that the grey tolerance rough set (GTRS) and construct the GTRS-based classifiers. Design/methodology/approach – The authors use grey relational analysis to implement a relationship-based similarity measure for tolerance rough sets. Findings – The proposed classification method has been tested on several real-world data sets. Its classification performance is comparable to that of other rough-set-based methods. Originality/value – The authors design a variant of a similarity measure which can be used to estimate the relationship between any two patterns, such that the closer the relationship, the greater the similarity will be.