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All Journal JOIV : International Journal on Informatics Visualization
Norlida Hassan
Universiti Tun Hussein Onn Malaysia, Johor, Malaysia
Computer Science & IT

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Exploratory Study of Kohonen Network for Human Health State Classification Hamijah Mohd Rahman; Nureize Arbaiy; Muhammad Shukeri Che Lah; Norlida Hassan
JOIV : International Journal on Informatics Visualization Vol 2, No 3-2 (2018): The Diversity in Information Systems
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (982.301 KB) | DOI: 10.30630/joiv.2.3-2.143

Abstract

Kohonen Network is an unsupervised learning which forms clusters from patterns that share common features and group similar patterns together. This network are commonly uses grids of artificial neurons which connected to all the inputs. This paper presents an exploratory study of Kohonen Neural Network to classify human health state. Neural Connection tool is used to generate the result based on Kohonen learning algorithm. Procedural steps are provided to assist the implementation of the Kohonen Network. The result shows that side 2 is more appropriate for this problem with efficient learning rate 1.0. It gives good distribution for training and test patterns. Study to the variation of dataset’s size will be considered in the near future to evaluate the performance of the network.
Co-Authors Hamijah Mohd Rahman Muhammad Shukeri Che Lah Nureize Arbaiy