Pattern classification using grey tolerance rough sets
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