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A novel approach for determining the optimal number of hidden layer neurons for FNN's and its application in data mining
Citation
Xu, S and Chen, L, A novel approach for determining the optimal number of hidden layer neurons for FNN's and its application in data mining, Proceedings The 5th International Conference on Information Technology and Applications, 23-26 June 2008, Carins, Qld, pp. 683-686. ISBN 978-0-9803267-2-7 (2008) [Refereed Conference Paper]
Copyright Statement
Copyright 2008 ICITA
Official URL: http://www.icita.org/previous/icita2008/abstracts/...
Abstract
Optimizing the number of hidden layer
neurons for an FNN (feedforward neural network) to
solve a practical problem remains one of the unsolved
tasks in this research area. In this paper we review
several mechanisms in the neural networks literature
which have been used for determining an optimal
number of hidden layer neuron (given an application),
propose our new approach based on some mathematical
evidence, and apply it in financial data mining.
Compared with the existing methods, our new approach
is proven (with mathematical justification), and can be
easily handled by users from all application fields.
Item Details
| Item Type: | Refereed Conference Paper |
|---|---|
| Keywords: | neural networks, data mining, number of hidden layer neurons |
| Research Division: | Information and Computing Sciences |
| Research Group: | Machine learning |
| Research Field: | Neural networks |
| Objective Division: | Information and Communication Services |
| Objective Group: | Information systems, technologies and services |
| Objective Field: | Information systems, technologies and services not elsewhere classified |
| UTAS Author: | Xu, S (Dr Shuxiang Xu) |
| ID Code: | 54013 |
| Year Published: | 2008 |
| Deposited By: | Information and Communication Technology |
| Deposited On: | 2009-02-06 |
| Last Modified: | 2014-10-20 |
| Downloads: | 91 View Download Statistics |
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