A wrapper method for feature selection using Support Vector Machines

被引：361

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

页码：2208 / 2217

页数：10

共 23 条

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