集成神经网络学习过程中采样方法的分析

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI:10.1109/NAFIPS.2007.383909

M. Lopez, P. Melin

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摘要

在开发集成神经网络的学习算法时，使用采样方法是至关重要的。本文比较分析了基于均方误差的集合神经网络采样方法和交叉验证采样方法。

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Analysis of sampling methods in the learning process of ensemble neural networks

When developing learning algorithms for ensemble neural networks it is of fundamental importance to use a sampling method. In this paper a comparative analysis is made, between a sampling data method based on the mean square error for the training of ensemble neural networks and cross validation sampling method.

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NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society

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