A new method for measuring uncertainty and fuzziness in rough set theory

2002333 citationsJournal Article

Authors

Jiye Liang · Shanxi University of Traditional Chinese Medicine

Kwai‐Sang Chin · City University of Hong Kong

Chuangyin Dang · City University of Hong Kong

Richard C.M. Yam · City University of Hong Kong

Abstract

Based on the complement behavior of information gain, a new definition of information entropy is proposed along with its justification in rough set theory. Some properties of this definition imply those of Shannon's entropy. Based on the new information entropy, conditional entropy and mutual information are then introduced and applied to knowledge bases. The new information entropy is proved to also be a fuzzy entropy. Keywords: Rough SetsInformation EntropyUncertaintyFuzzinessRough ClassificationData Analysis

Topics & Keywords

Rough Sets and Fuzzy Logic Advanced Computational Techniques and Applications Extenics and Innovation Methods

UN Sustainable Development Goals

Reduced inequalities

Publication Details

Published in: International Journal of General Systems

Volume 31, Issue 4, pp. 331-342

DOI: 10.1080/0308107021000013635

Field-Weighted Citation Impact: 1.40