| 基于MTS特征选择的神经网络集成方法 |
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| 引用本文： | 时建中,程龙生,牛俊磊,郭志芳.基于MTS特征选择的神经网络集成方法[J].数学的实践与认识,2012,42(6):164-168. |
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| 作者姓名： | 时建中 程龙生 牛俊磊 郭志芳 |
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| 作者单位： | 南京理工大学经济管理学院,江苏南京,210094 |
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| 基金项目： | 教育部人文社会科学研究规划基金，国家自然科学基金，江苏省社会科学基金，南京理工大学自主科研专项计划 |
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| 摘 要： | 在Bagging算法基础上,运用马田系统进行特征选择,形成双重扰动改善神经网络集成的分类性能.实验表明,双重扰动增加了集成网络个体精度和差异度,基于MTS-Bagging算法的分类性能相比于Bagging有明显提高.
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| 关 键 词： | 神经网络集成 马田系统 特征选择 MTS-Bagging |
Feature Selection based on Mahalanobis-Taguchi System for Neural Network Ensemble Method |
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| SHI Jian-zhong
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CHENG Long-sheng
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Niu Jun-lei
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GUO Zhi-fang.Feature Selection based on Mahalanobis-Taguchi System for Neural Network Ensemble Method[J].Mathematics in Practice and Theory,2012,42(6):164-168. |
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| Authors: | SHI Jian-zhong CHENG Long-sheng Niu Jun-lei GUO Zhi-fang |
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| Institution: | (School of Economics and Management,Nanjing University of Science and Technology,Nanjing 210094,China) |
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| Abstract: | To improve the classification ability of ensemble neural networks,MahalanobisTaguchi System is used for features selection based on Bagging algorithm.Experiment results show that the double disturbance increase classification ability and difference of the individual network.The classification ability of proposed method outperforms Bagging algorithm. |
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| Keywords: | neural network ensemble Mahalanobis-Taguchi system features selection MTSBagging |
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