Enhance generalized learning vector quantization using unsupervised extreme learning machine and intelligent K-means clustering

M. Anwar Ma'sum, Dewa Made Sri Arsa, Novian Habibie, Wisnu Jatmiko

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

In this paper we proposed an enhancement of GLVQ classifier using USELM and IK-Means clustering. USELM is used to transform feature data into more separable form. The clustering method used to initiate codebook during training process. The proposed method has been tested using synthetic dataset and benchmark dataset. The proposed method has been compared to previous method and commonly used method. Experiment result shows that in over all dataset, the proposed method still has highest accuracy compared to others. Compared to GLVQ based classifier, the proposed method has better accuracy with margin 7.42%, 10.29%, 11.80%, and 8.11% for GLVQ, FNGLVQ, IK-Means-GLVQ, and USELM-GLVQ respectively. Compared to commonly used classifiers the proposed method has better accuracy with margin 1.94%, 2.93%, 11.61%, 31.37%, and 2.91% for MLP, Tree (J48), Linear-SVM, Sigmoid-SVM, and RBF-SVM respectively.

Original languageEnglish
Title of host publicationProceedings - WBIS 2017
Subtitle of host publication2017 International Workshop on Big Data and Information Security
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages77-83
Number of pages7
ISBN (Electronic)9781538620380
DOIs
Publication statusPublished - 29 Jan 2018
Event2017 International Workshop on Big Data and Information Security, WBIS 2017 - Jakarta, Indonesia
Duration: 23 Sep 201724 Sep 2017

Publication series

NameProceedings - WBIS 2017: 2017 International Workshop on Big Data and Information Security
Volume2018-January

Conference

Conference2017 International Workshop on Big Data and Information Security, WBIS 2017
CountryIndonesia
CityJakarta
Period23/09/1724/09/17

Keywords

  • GLVQ
  • IK-Means
  • USELM
  • enhancement

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  • Cite this

    Ma'sum, M. A., Arsa, D. M. S., Habibie, N., & Jatmiko, W. (2018). Enhance generalized learning vector quantization using unsupervised extreme learning machine and intelligent K-means clustering. In Proceedings - WBIS 2017: 2017 International Workshop on Big Data and Information Security (pp. 77-83). (Proceedings - WBIS 2017: 2017 International Workshop on Big Data and Information Security; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWBIS.2017.8275106