Accession number:20090211849841
Title: The choquet integral with respect to R-measure based on
γ-support
Authors:Liu, Hsiang-Chuan (1); Tu, Yu-Chieh (2); Huang, Wen-Chun (2); Chen, Chin-Chun (2)
Author affiliation:(1) Department of Bioinformatics, Asia University, Taiwan; (2) Graduate Institute of Educational Measurement and Statistics, Taichung University, Taiwan; (3) General Education, Min- Hwei College of Health Care Management, Taiwan
Corresponding author:Liu, H.-C.
Source title:Proceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Abbreviated source title:Proc. - Int. Conf. Fuzzy Syst. Knowl. Discov., FSKD
Volume:1
Monograph title:Proceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Issue date:2008
Publication year:2008 Pages:645-649
Article number:4666055 Language:English
ISBN-13:9780769533056
Document type:Conference article (CA)
Conference name:5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Conference date:October 18, 2008 - October 20, 2008 Conference location:Jinan, Shandong, China
Conference code:74641
Publisher:Inst. of Elec. and Elec. Eng. Computer Society, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States Abstract:When the multicollinearity within independent variables occurs in the multiple regression models, its performance will always be poor. Replacing the above models with the ridge
regression model is the traditional improved method. In our previous work, we found that, the Choquet integral regression model with
λ-measure based on the new support, γ-support, proposed by us has the best performance than before. In this study, for finding the further improved model, we replaced two well known fuzzy measures, P-measure and λ-measure with our new fuzzy measure, R-measure in Choquet integral regression model with the new support, γ-support. For comparing the Choquet integral regression model with P-measure, λ- measure and R-measure based on two different fuzzy supports, V- support and γ-support, respectively, the traditional multiple regression model and the ridge regression model, a real data
experiment by using a 5-fold cross-validation mean square error (MSE) is conducted. Experimental result shows that the Choquet integral regression model with R-measure based on γ- support has the best performance. © 2008 IEEE.
Number of references:10
Main heading:Regression analysis
Controlled terms:Fuzzy logic - Fuzzy systems - Integral equations - Mathematical models - Mean square error
Uncontrolled terms:Choquet integrals - Cross validations - Fuzzy measures - Improved methods - Improved models - Independent variables - Mean squares - Multicollinearity - Multiple regression models - Real datums - Regression models - Ridge regressions Classification code:922.2 Mathematical Statistics - 921.4
Combinatorial Mathematics, Includes Graph Theory, Set Theory - 921.2 Calculus - 961 Systems Science - 921 Mathematics - 723.4 Artificial Intelligence - 721.1 Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory - 731.1 Control Systems
DOI:10.1109/FSKD.2008.545 Database:Compendex
Compilation and indexing terms, Copyright 2009 Elsevier Inc.
