DocumentCode
3751992
Title
Multi codebook LVQ-based artificial neural network using clustering approach
Author
M. Anwar Ma´sum;H. R. Sanabila;W. Jatmiko; Aprinaldi
Author_Institution
Faculty of Computer Science Universitas Indonesia
fYear
2015
Firstpage
263
Lastpage
268
Abstract
In this paper we proposed multicodebook LVQ-based artificial neural network classifier using clustering approach. The classifiers are LVQ, LVQ2-1, GLVQ, and FNGLVQ. The clustering algorithm used to build multi codebook is K-Means, IK-Means, and GMM. Experiment result shows that on synthteic dataset multi codebook FNGLVQ using GMM clustering has higest improvement with 19,53% mprovement compared to FNGLVQ. Whereas on bencmark dataset multi codebook LVQ2-1 using K-Means clustering has higest improvement with 5,83% improvement cmpared to LVQ-2.1.
Keywords
"Benchmark testing","Iris","Ionosphere","Cancer"
Publisher
ieee
Conference_Titel
Advanced Computer Science and Information Systems (ICACSIS), 2015 International Conference on
Type
conf
DOI
10.1109/ICACSIS.2015.7415193
Filename
7415193
Link To Document