Ensemble of GA Based Selective Neural Network Ensembles
Neural network ensemble is a learning paradigm where several neural networks are jointly used to solve a problem. In this paper, e-GASEN, a two-layer neural network ensemble architecture is proposed, in which the base learners of the final ensemble are also ensembles. Experimental results show that e-GASEN generalizes better than a popular ensemble method. The reason why e-GASEN works is also discussed. We believe that the different layers of e-GASEN attain good generalization ability for different reasons. The first layer ensembles profit from the selected individual neural networks that are moderately divergent but generalize well, while the second layer ensemble profits from the divergency among the first layer ensembles.
Jian-Xin WU Zhi-Hua ZHOU Zhao-Qian CHEN
National Laboratory for Novel Software Technology Nanjing University Nanjing, 210093, P.R.China
国际会议
8th International Conference on Neural Information Processing(ICONIP 2001)(第八届国际神经信息处理大会)
上海
英文
1515-1520
2001-11-14（万方平台首次上网日期，不代表论文的发表时间）