학술논문

Multiple SVM classification syatem based on Choquet integral with respect to composed measure of L-measure and Delta-measure
Document Type
Conference
Source
2010 International Conference on Machine Learning and Cybernetics Machine Learning and Cybernetics (ICMLC), 2010 International Conference on. 5:2396-2401 Jul, 2010
Subject
Computing and Processing
Communication, Networking and Broadcast Technologies
Support vector machines
Classification algorithms
Kernel
Training
Machine learning
Accuracy
Polynomials
SVM
Fuzzy integral
Fuzzy fusion
L-measure
Language
ISSN
2160-133X
2160-1348
Abstract
In order to overcome the situation that interactions exist between all classifiers from multiple classification system. In this study, we fuse the multiple SVM classifiers by fuzzy fusion algorithm with respect to a novel composed measure of L-measure and Delta (δ)-measure. We expect to gain a more accurate classification than single SVM and other combination method, like majority vote. From the experiment results, the fusion method based on the fuzzy fusion algorithm with respect to composed measure obtains advancement in terms of the performance of classification.