| 一种动态性神经网络的集成方法 |
| |
| 引用本文： | 郑建军,刘玉树,刘琼昕,孙曼.一种动态性神经网络的集成方法[J].计算机工程,2004,30(3):49-50,182. |
| |
| 作者姓名： | 郑建军 刘玉树 刘琼昕 孙曼 |
| |
| 作者单位： | 北京理工大学信息科学技术学院计算机科学工程系,北京,100081 |
| |
| 摘 要： | 提出一种动态性神经网络集成方法，该方法针对若干不同的神经网络，采用加权最近邻技术收集它们的泛化误差信息构成性能矩阵，在此基础上动态选择泛化误差较小的神经网络，经过动态平均形成集成的最终输出结果。实验表明，与其它方法相比，该方法具有令人满意的性能。
|
| 关 键 词： | 神经网络 动态集成 泛化误差 预测 |
| 文章编号： | 1000-3428(2004)03-0049-02 |
A Dynamic Integration Approach for a Neural Network Ensemble |
| |
| ZHENG Jianjun,LIU Yushu,LIU Qiongxin,SUN Man.A Dynamic Integration Approach for a Neural Network Ensemble[J].Computer Engineering,2004,30(3):49-50,182. |
| |
| Authors: | ZHENG Jianjun LIU Yushu LIU Qiongxin SUN Man |
| |
| Abstract: | A dynamic integration approach for a neural network ensemble is presented, which makes use of weighted nearest neighbor method to collect information about the generalization errors of some different NNs into a performance matrix, and then the NNs with low local generalization errors are dynamically selected and locally dynamic averaging is applied to the NNs in order to conduct the final results of the ensemble. In the experiments, this approach shows promising results on performance compared with other methods. |
| |
| Keywords: | Neural network(NN) Dynamic integration Generalization error Prediction |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
