Pattern recognition from neural network with functional dependency preprocessing

被引：0

作者：

Wong, MT ^{[1
]}

Geva, S ^{[1
]}

Orlowski, M ^{[1
]}

机构：

[1] Queensland Univ Technol, Fac Informat Technol, Neurocomp Res Ctr, Brisbane, Qld 4001, Australia

来源：

IEEE TENCON'97 - IEEE REGIONAL 10 ANNUAL CONFERENCE, PROCEEDINGS, VOLS 1 AND 2: SPEECH AND IMAGE TECHNOLOGIES FOR COMPUTING AND TELECOMMUNICATIONS | 1997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：

This paper describes how the functional dependency preprocessing technique can he used to enhance the performance of pattern recognition from trained artificial neural network. By identifying the functional dependencies of a data set prior to network training, a subset of attributes of the data set can be found which can determine the classification attribute. Experimental results indicate that it can lead to faster network training, smaller neural network size and better (or at least equal) generalization accuracy of the network.

引用

页码：387 / 390

页数：4