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

页码：263 / 268

页数：6

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