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
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"
Conference_Titel :
Advanced Computer Science and Information Systems (ICACSIS), 2015 International Conference on
DOI :
10.1109/ICACSIS.2015.7415193