Summary
International Symposium on Nonlinear Theory and its Applications
2010
Session Number:C3L-C
Session:
Number:C3L-C3
A Classification System based on Collaboration of Adaptive Resonance Theory Maps and Learning Vector Quantization
Yoko Enosawa, Haruna Matsushita, Toshimichi Saito,
pp.611-614
Publication Date:2010/9/5
Online ISSN:2188-5079
DOI:10.34385/proc.44.C3L-C3
PDF download (138.3KB)
Summary:
This paper studies a novel classification system with unsupervised learning. First, the adaptive resonance theory map is used to make categories for input sate. After that the learning vector quantization decides the category borders. In elementary classification problems, algorithm works better as the problem complexity increases.