An artificial neural network model for multi dimension reduction and data structure exploration, Proceedings of International Conference of Soft Computing and Pattern Recognition (SoCPaR 2009), December 4-7, 2009

Teh, Chee Siong and Ming Leong, Yii and Chen, Chwen Jen (2009) An artificial neural network model for multi dimension reduction and data structure exploration, Proceedings of International Conference of Soft Computing and Pattern Recognition (SoCPaR 2009), December 4-7, 2009. In: Proceedings of International Conference of Soft Computing and Pattern Recognition (SoCPaR 2009), December 4-7, 2009.

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Abstract

This paper proposes an hybrid artificial neural network (ANN) with self-organizing map (SOM) and modified adaptive coordinates (AC) for multivariate dimension reduction and data structures exploration. SOM, being a prominent unsupervised learning algorithm, is often used for multivariate data visualization. However, SOM only preserved input space inter-neurons distances and not in the output space because of SOM rigid grid. SOM grid provides little information for visual exploration of the clustering tendency of the multivariate data. Modified AC is therefore proposed to remove SOM's map rigidity and provides better data topology preserved visualization. Empirical study of the hybrid yielded promising topology preserved visualizations for synthetic and benchmarking datasets.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Artificial Neural Network Model, soft computing, technology, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak
Subjects: L Education > L Education (General)
T Technology > T Technology (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Cognitive Sciences and Human Development
Depositing User: George Gerrie
Date Deposited: 05 Jan 2016 01:57
Last Modified: 05 Jan 2016 01:57
URI: http://ir.unimas.my/id/eprint/9982

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