A wrapper method for feature selection using Support Vector Machines

被引：341
|
作者：
Maldonado, Sebastian [1 ]
Weber, Richard [1 ]
机构：
[1] Univ Chile, Dept Ind Engn, Santiago, Chile
来源：
INFORMATION SCIENCES | 2009年 / 179卷 / 13期
关键词：
Feature selection; Wrapper methods; Classification; Support Vector Machines; Mathematical programming;
D O I：
10.1016/j.ins.2009.02.014
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We introduce a novel wrapper Algorithm for Feature Selection, using Support Vector Machines with kernel functions. Our method is based on a sequential backward selection, using the number of errors in a validation subset as the measure to decide which feature to remove in each iteration. We compare our approach with other algorithms like a filter method or Recursive Feature Elimination SVM to demonstrate its effectiveness and efficiency. (C) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码：2208 / 2217
页数：10
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