Analysis of Feature Weighting Methods Based on Feature Ranking Methods for Classification

被引：0

作者：

Jankowski, Norbert ^{[1
]}

Usowicz, Krzysztof ^{[1
]}

机构：

[1] Nicolaus Copernicus Univ, Dept Informat, Torun, Poland

来源：

NEURAL INFORMATION PROCESSING, PT II | 2011年 / 7063卷

关键词：

Feature weighting; feature selection; computational intelligence; INFORMATION;

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 and analyze new fast feature weighting algorithms based on different types of feature ranking. Feature weighting may be much faster than feature selection because there is no need to find cut-threshold in the raking. Presented weighting schemes may be combined with several distance based classifiers like SVM, kNN or RBF network (and not only). Results shows that such method can be successfully used with classifiers.

引用

页码：238 / 247

页数：10

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