Greedy Binary Search and Feature Subset Selection

被引：0

作者：

Han, Myung-Mook ^{[1
]}

Li, Dong-hui ^{[1
]}

机构：

[1] KyungWon Univ, Dept Comp Software, Coll IT, Songnam 461701, Kyunggi Do, South Korea

来源：

INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL | 2009年 / 12卷 / 06期

关键词：

Feature selection; Classification; Data mining; Greedy binary search; ALGORITHMS;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In this paper, we propose new Greedy Binary Search methods, Greedy Binary Search (GBS) and Greedy Binary Search with Parameter(PGBS), to be used for feature selection problem. We describe the traditional algorithms including SFS (SBS), GSFS (GSBS), PTA (l, s) (GPTA (l, s)) and SFFS (SBFS). We also explain our proposed methods and compare them with the time complexity. Through a variety of experiments and analysis, it is found that our methods outperform traditional algorithms in terms of the number of features and the correct classification rate.

引用

页码：1379 / 1395

页数：17

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