Proceedings of the IEEK Conference (대한전자공학회:학술대회논문집)
- 2002.06c
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- Pages.9-12
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- 2002
Improving effective Learning Performance of Kernel method
커널 메소드의 효과적인 학습 성능 향상
Abstract
This paper proposes a dynamic moment algorithm to control oscillaion before the convergence of the KR(Kernel Relaxation). The proposed dynamic moment algorithm can be controlled to convergence speed and performance according to the change of the dynamic moment by teaming training. we used SONAR data that is a neural network classifier standard evaluation data in order to do impartial performance evaluation. The proposed algorithm has been applied to the KP (kernel perceptron), KPM(kernel perceptron with margin) and KLMS(kernel lms) as the kernel method presented recently. The simulation results of proposed algorithm have better the convergence performance than those using none and static moment.
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