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Pattern classification using grey tolerance rough sets

Yi-Chung Hu (Department of Business Administration, Chung Yuan Christian University, Chung Li Dist., Taoyuan City, Taiwan)

Kybernetes

ISSN: 0368-492X

Article publication date: 1 February 2016

171

Abstract

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.

Keywords

Acknowledgements

The author thanks the anonymous referees for their valuable comments. This research is partially supported by the Ministry of Science and Technology of Taiwan under grant MOST 104-2410-H-033-023-MY2.

Citation

Hu, Y.-C. (2016), "Pattern classification using grey tolerance rough sets", Kybernetes, Vol. 45 No. 2, pp. 266-281. https://doi.org/10.1108/K-04-2015-0105

Publisher

:

Emerald Group Publishing Limited

Copyright © 2016, Emerald Group Publishing Limited

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