Feature selection using radial basis function networks

被引：13

作者：

Basak, J ^{[1
]}

Mitra, S ^{[1
]}

机构：

[1] Indian Stat Inst, Machine Intelligence Unit, Kolkata 700035, W Bengal, India

来源：

NEURAL COMPUTING & APPLICATIONS | 1999年 / 8卷 / 04期

关键词：

feature evaluation index; feature selection; Radial Basis Function network;

D O I：

10.1007/s005210050035

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A new method of feature selection using a Radial Basis Function network is described. The parameters of the radial basis function network, in general form a compact description of class structures. The intraclass and interclass distances are expressed in terms of the parameters of the trained network, and two different feature evaluation indices are derived from these distances. The effectiveness of the algorithm is demonstrated on Iris and speech data, and a comparative study is provided with several existing techniques.

引用

页码：297 / 302

页数：6

共 19 条

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