TY - GEN
T1 - Multi codebook LVQ-based artificial neural network using clustering approach
AU - Ma'Sum, M. Anwar
AU - Sanabila, H. R.
AU - Jatmiko, Wisnu
AU - Aprinaldi,
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/2/19
Y1 - 2016/2/19
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84964466690&partnerID=8YFLogxK
U2 - 10.1109/ICACSIS.2015.7415193
DO - 10.1109/ICACSIS.2015.7415193
M3 - Conference contribution
AN - SCOPUS:84964466690
T3 - ICACSIS 2015 - 2015 International Conference on Advanced Computer Science and Information Systems, Proceedings
SP - 263
EP - 268
BT - ICACSIS 2015 - 2015 International Conference on Advanced Computer Science and Information Systems, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - International Conference on Advanced Computer Science and Information Systems, ICACSIS 2015
Y2 - 10 October 2015 through 11 October 2015
ER -