Feature selection algorithms for the generation of multiple classifier systems and their application to handwritten word recognition

被引：33

作者：

Günter, S ^{[1
]}

Bunke, H ^{[1
]}

机构：

[1] Univ Bern, Dept Comp Sci, CH-3012 Bern, Switzerland

来源：

PATTERN RECOGNITION LETTERS | 2004年 / 25卷 / 11期

基金：

瑞士国家科学基金会;

关键词：

classifier combination; ensemble creation method; feature selection; handwritten word recognition; hidden Markov model (HMM);

D O I：

10.1016/j.patrec.2004.05.002

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The study of multiple classifier systems has become an area of intensive research in pattern recognition recently. Also in handwriting recognition, systems combining several classifiers have been investigated. In this paper new methods for the creation of classifier ensembles based on feature selection algorithms are introduced. Those new methods are evaluated and compared to existing approaches in the context of handwritten word recognition, using a hidden Markov model recognizer as basic classifier. (C) 2004 Elsevier B.V. All rights reserved.

引用

页码：1323 / 1336

页数：14

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