Accession number:20090111824569
Title:The choquet integral with respect to λ,-measure based on γ-support
Authors:Liu, Hsiang-Chuan (1); Tu, Yu-Chieh (2); Chen, Chin-Chun (2); Weng, Wei-Sheng (2)
Author affiliation:(1) Department of Bioinformatics, Asia University, Taiwan; (2) Graduate Institute of Educational Measurement and Statistics, National Taichung University, Taiwan; (3) General Education, Min-Hwei College of Health Care Management, Taiwan Corresponding author:Liu, H.-C.
Source title:Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
Abbreviated source title:Proc. Int. Conf. Mach. Learn. Cybern., ICMLC Volume:6
Monograph title:Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
Issue date:2008
Publication year:2008 Pages:3602-3606
Article number:4621029 Language:English
ISBN-13:9781424420964
Document type:Conference article (CA)
Conference name:7th International Conference on Machine Learning and Cybernetics, ICMLC
Conference date:July 12, 2008 - July 15, 2008 Conference location:Kunming, China
Conference code:74802
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 between independent variables occurs in the multiple regression models, its performance will
always be poor. The traditional improved method which is always used is the ridge regression model. Recently, the Choquet integral regression model with fuzzy measure can further be exploited to improve this situation. In this study, we found that based on
different fuzzy support, the Choquet integral regression model with the same fuzzy measure may have different performances, three kinds of fuzzy supports, C-support, V-support and γ-support proposed by our work were considered. For evaluating the
performances of the Choquet integral regression models with P- measure or λ-measure based on above different fuzzy supports, 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 λ-measure based on γ-support has the best performance. © 2008 IEEE.
Number of references:9
Main heading:Regression analysis
Controlled terms:Control theory - Cybernetics - Integral equations - Learning systems - Mean square error - Robot learning
Uncontrolled terms:C-support - Choquet integrals - Cross validations - Fuzzy measure - Fuzzy support - Improved methods - Independent variables - Mean squares - Multicollinearity - Multiple regression models - Real datums - Regression models - Ridge regressions - V- support
Classification code:921.2 Calculus - 731.5 Robotics - 731.1 Control Systems - 922.2 Mathematical Statistics - 723.5 Computer
Applications - 461.9 Biology - 461.4 Ergonomics and Human Factors Engineering - 723.4 Artificial Intelligence
DOI:10.1109/ICMLC.2008.4621029 Database:Compendex
Compilation and indexing terms, Copyright 2009 Elsevier Inc.
