An Learning Algorithm to find the Optimized Network Structure in an Incremental Model

Lee Jong-Chan; Cho Sang-Yeop

An Learning Algorithm to find the Optimized Network Structure in an Incremental Model

Lee Jong-Chan, Cho Sang-Yeop, Journal of Internet Computing and Services, Vol. 4, No. 5, pp. 69-76, Oct. 2003
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Keywords: Pattern Classification, Incremental Learning, Pruning Method, Optimized Network Structure

Abstract

In this paper we show a new learning algorithm for pattern classification. This algorithm considered a scheme to find a solution to a problem of incremental learning algorithm when the structure becomes too complex by noise patterns included in learning data set. Our approach for this problem uses a pruning method which terminates the learning process with a predefined criterion. In this process, an iterative model with 3 layer feedforward structure is derived from the incremental model by an appropriate manipulations. Notice that this network structure is not full-connected between upper and lower layers. To verify the effectiveness of pruning method, this network is retrained by EBP. From this results, we can find out that the proposed algorithm is effective, as an aspect of a system performence and the node number included in network structure.

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Cite this article

[APA Style]

Jong-Chan, L. & Sang-Yeop, C. (2003). An Learning Algorithm to find the Optimized Network Structure in an Incremental Model. Journal of Internet Computing and Services, 4(5), 69-76.

[IEEE Style]

L. Jong-Chan and C. Sang-Yeop, "An Learning Algorithm to find the Optimized Network Structure in an Incremental Model," Journal of Internet Computing and Services, vol. 4, no. 5, pp. 69-76, 2003.

[ACM Style]

Lee Jong-Chan and Cho Sang-Yeop. 2003. An Learning Algorithm to find the Optimized Network Structure in an Incremental Model. Journal of Internet Computing and Services, 4, 5, (2003), 69-76.