Quantitative feature evaluation using hybrid neural network and fuzzy logic approach

被引：0

作者：

Jiang, H ^{[1
]}

Feng, X ^{[1
]}

机构：

[1] Marquette Univ, Dept Elect & Comp Engn, Milwaukee, WI 53201 USA

来源：

PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS 2003, VOLS 1-4 | 2003年

关键词：

neural networks; fuzzy logic; competitive learning; feature evaluation;

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 paperpresents a hybrid feature evaluation method using competitive learning neural network and fuzzy logic for the analysis of high dimensional data. Not only. we can give the quantitative information of the relative importance of features but the contributions of features to each data category can be observed during the analysis. The motivation of this study is to provide a method to discover the nature of data represented by multiple features by evaluating the importance of features representing data and the data best describing the information embedded by features.

引用

页码：421 / 425

页数：5