Classification by means of evolutionary product-unit neural networks

被引：0

作者：

Hervas, Cesar ^{[1
]}

Martinez, Francisco J. ^{[2
]}

Gutierrez, Pedro A. ^{[2
]}

机构：

[1] ETEA, Dept Management & Quantitat Methods, Escritor Castilla Aguayo 4, Cordoba 14005, Spain

[2] Univ Cordoba, Dept Comp & Numerical Analysis, E-14071 Cordoba, Spain

来源：

2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10 | 2006年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We propose a classification method based on a special class of feed-forward neural network, namely product-unit neural networks. They are based on multiplicative nodes instead of additive ones, where the nonlinear basis functions express the possible strong interactions among the variables. We apply an evolutionary algorithm to determine the basic structure of the product-unit model and to estimate the coefficients of the model. The empirical results show that the proposed model is very promising in terms of classification accuracy, yielding a state-of-the-art performance.

引用

页码：1525 / +

页数：3

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