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http://dx.doi.org/10.5391/JKIIS.2003.13.6.655

Import Vector Voting Model for Multi-pattern Classification  

Choi, Jun-Hyeog (김포대학 컴퓨터계열)
Kim, Dae-Su (한신대학교 컴퓨터학과)
Rim, Kee-Wook (선문대학교 지식정보산업공학과)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.13, no.6, 2003 , pp. 655-660 More about this Journal
Abstract
In general, Support Vector Machine has a good performance in binary classification, but it has the limitation on multi-pattern classification. So, we proposed an Import Vector Voting model for two or more labels classification. This model applied kernel bagging strategy to Import Vector Machine by Zhu. The proposed model used a voting strategy which averaged optimal kernel function from many kernel functions. In experiments, not only binary but multi-pattern classification problems, our proposed Import Vector Voting model showed good performance for given machine learning data.
Keywords
Kernel Bagging; Multi-pattern Classification; Import Vector Voting Model;
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