A Fuzzy Random Variable Approach to Restructuring of Rough Sets through Statistical Test

Authors:
Junzo Watada;Lee-Chuan Lin;Minji Qiang;Pei-Chun Lin
Affiliations:
Graduate School of Information, Production and Systems, Waseda University, Fukuoka, Japan 808-0135;Graduate School of Information, Production and Systems, Waseda University, Fukuoka, Japan 808-0135;Graduate School of Information, Production and Systems, Waseda University, Fukuoka, Japan 808-0135;Graduate School of Information, Production and Systems, Waseda University, Fukuoka, Japan 808-0135
Venue:
RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Year:
2009

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Abstract

Usually it is hard to classify the situation where randomness and fuzziness exist simultaneously. This paper presents a method based on fuzzy random variables and statistical t-test to restructure a rough set. The algorithms of rough set and statistical t-test are used to distinguish whether a subset can be classified in the object set or not. The expected-value-approach is also applied to calculate the fuzzy value with probability into a scalar value.