Proceedings of the IEEK Conference (대한전자공학회:학술대회논문집)
- 1998.10a
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- Pages.1277-1280
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- 1998
A Structural Learning of MLP Classifiers Using PfSGA
PfSGA를 이용한 MLP 분류기의 구조 학습
Abstract
We propose a structural learning method of MLP classifiers for a given application using PfSGA (parameter-free species genetic algorithm), which is a combining of species genetic algorithm(SGA) and parameter-free genetic algorithm(PfGA). experimental results show that PfSGA can reduce the learing time of SGA and has no influence of parameter values on structural learning. And we also convince that PfSGA is more efficient than the other methods in the aspect of misclassification ratio, learning rate, and complexity of MLP structure.
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