FEATURE-SELECTION BASED ON THE STRUCTURAL INDEXES OF CATEGORIES

被引：20

作者：

KUDO, M

SHIMBO, M

机构：

[1] Department of Information Engineering, Faculty of Engineering, Hokkaido University, Sapporo

来源：

PATTERN RECOGNITION | 1993年 / 26卷 / 06期

关键词：

FEATURE SELECTION; SUBCLASS METHOD; PEAKING PHENOMENA; STRUCTURAL INDEXES; HYPERRECTANGLES;

D O I：

10.1016/0031-3203(93)90055-2

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 technique is proposed to select features out of all available ones on the basis of structural indices of categories. In terms of hyper-rectangles including as many training samples of a category as possible, two characteristic indices are calculated which summarize its underlying distribution of samples. The hyper-rectangles and the indices are available in evaluating the degree of importance of features, and are used to increase the discrimination rates of discrimination rules by removing redundant features. The running time of the algorithm is linear order in the number of features. Experiments on artificial and real data attests its effectiveness.

引用

收藏

页码：891 / 901

页数：11

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