On a Criterion for Evaluating the Accuracy of Approximation by Variable Precision Rough Sets

We introduce a new criterion for evaluating the accuracy of approximation in variable precision rough set models. The authors have proposed an evaluation criterion of relative reducts in Pawlak’s rough sets, which is based on counting equivalent classes that are used for upper approximations constructed from relative reducts. By introducing this idea to evaluation of the accuracy of approximation, the proposed criterion evaluates the accuracy of approximation by the average certainty scores of equivalent classes that are used in β -lower approximations and β -upper approximations, respectively.

Authors and Affiliations

1. College of Information and Systems, Muroran Institute of Technology, 27-1 Mizumoto, Muroran, 050-8585, Japan

   Yasuo Kudo

2. Graduate School of Information Science and Technology, Hokkaido University, Kita 14,Nishi 9, Kita-ku, Sapporo, 060-0814, Japan

   Tetsuya Murai

Editors and Affiliations

1. School of Knowledge Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, 923-1292, Ishikawa, Japan

   Van-Nam Huynh  & Yoshiteru Nakamori  & 

2. Department of Engineering Mathematics, University of Bristol, Queen’s Building, University Walk, BS8 1TR, Bristol, United Kingdom

   Jonathan Lawry

3. Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama, Toyonaka, 560-8531, Osaka, Japan

   Masahiro Inuiguchi

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