Citation

Goh, Pey Yun and Tan, Shing Chiang and Cheah, Wooi Ping (2014) A nodes reduction procedure for RBFNDDA through histogram. In: Neural Information Processing. Lecture Notes in Computer Science (8834). Springer International Publishing, pp. 127-134. ISBN 978-3-319-12636-4

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Abstract

This paper presents a two-stage learning algorithm to reduce the hidden nodes of a radial basis function network (RBFN). The first stage involves the construction of an RBFN using the dynamic decay adjustment (DDA) and the second stage involves the use of a modified histogram algorithm (HIST) to reduce hidden neurons. DDA enables the RBFN to perform constructive learning without pre-defining the number of hidden nodes. The learning process of DDA is fast but it tends to generate a large network architecture as a result of its greedy insertion behavior. Therefore, an RBFNDDA-HIST is proposed to reduce the nodes. The proposed RBFNDDA-HIST is tested with three benchmark medical datasets. The experimental results show that the accuracy of the RBFNDDA-HIST is compatible with to that of RBFNDDA but with less number of nodes. This proposed network is favorable in a real environment because the computation cost can be reduced.

Item Type:	Book Section
Additional Information:	Book Subtitle: 21st International Conference, ICONIP 2014, Kuching, Malaysia, November 3-6, 2014. Proceedings, Part I
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	12 Feb 2015 06:54
Last Modified:	12 Feb 2015 06:54
URII:	http://shdl.mmu.edu.my/id/eprint/5974

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