The Mixture of Neural Networks Adapted to Multilayer Feedforward Architecture

被引:0
作者
Torres-Sospedra, Joaquin [1 ]
Hernandez-Espinosa, Carlos [1 ]
Fernandez-Redondo, Mercedes [1 ]
机构
[1] Univ Jaume 1, Dept Ingn & Ciencia Computadores, Castellon de La Plana 12071, Spain
来源
INTELLIGENT COMPUTING, PART I: INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING, ICIC 2006, PART I | 2006年 / 4113卷
关键词
D O I
10.1007/11816157_61
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The Mixture of Neural Networks (MixNN) is a Multi-Net System based on the Modular Approach. The MixNN employs a neural network to weight the outputs of the expert networks. This method decompose the original problem into subproblems, and the final decision is taken with the information provided by the expert networks and the gating network. The neural networks used in MixNN are quite simple so we present a mixture of networks based on the Multilayer Feedforward architecure, called Mixture of Multilayer Feedforward (MixMF). Finally, we have performed a comparison among Simple Ensemble, MixNN and MixMF. The methods have been tested with six databases from the UCI repository and the results show that MixMF is the best performing method.
引用
收藏
页码:488 / 493
页数:6
相关论文
共 8 条
  • [1] [Anonymous], 1996, ICML 96
  • [2] [Anonymous], 1999, Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems
  • [3] Hernández-Espinosa C, 2005, IEEE IJCNN, P1120
  • [4] HERNANDEZESPINO.C, 2005, LECT NOTES COMPUTER, V3316, P744
  • [5] Kuncheva LI., 2004, COMBINING PATTERN CL, DOI [DOI 10.1002/0471660264, 10.1002/0471660264]
  • [6] Newman D.J., 1998, UCI REPOSITORY MACHI
  • [7] Raviv Y., 1996, CONNECT SCI, V8, P356
  • [8] Tumer K., 1996, Connection Science, V8, P385, DOI 10.1080/095400996116839