Multi Codebook LVQ-Based Artificial Neural Network Using Clustering Approach

被引：0
|
作者：
Ma'sum, M. Anwar [1 ]
Sanabila, H. R. [1 ]
Jatmiko, W. [1 ]
Aprinaldi [1 ]
机构：
[1] Univ Indonesia, Fac Comp Sci, Depok, Indonesia
来源：
2015 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER SCIENCE AND INFORMATION SYSTEMS (ICACSIS) | 2015年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper we proposed multicodebook L VQ-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, IKMeans, and GMM. Experiment result shows that on synthteic dataset multi codebook FNGLVQ using GMM clustering has higest improvement with 19,53% mprovement compared to FNGL VQ. Whereas on bencmark dataset multi codebook L VQ2-1 using K-Means clustering has higest improvement with 5,83% improvement cmpared to LVQ-2.1
引用
收藏
页码：263 / 268
页数：6
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