Towards a Memetic Feature Selection Paradigm [Application Notes]

Author

Zhu, Zexuan ; Jia, Sen ; Ji, Zhen

Author_Institution

Shenzhen Univ., Shenzhen, China

Volume

5

Issue

2

fYear

2010

fDate

5/1/2010 12:00:00 AM

Firstpage

41

Lastpage

53

Abstract

Feature selection has become the focus of many real-world application oriented developments and applied research in recent years. With the rapid advancement of computer and database technologies, problems "with hundreds and thousands of variables or features are now ubiquitous in pattern recognition, data mining, and machine learning [1], [2]. In this article, we consider two real-world feature selection applications: gene selection in cancer classification based on microarray data and band selection for pixel classification using hyperspectral imagery data.

Keywords

cancer; data mining; feature extraction; image classification; learning (artificial intelligence); medical image processing; band selection; cancer classification; data mining; feature selection; gene selection; hyperspectral imagery data; machine learning; microarray data; pattern recognition; pixel classification; Application software; Cancer; Data mining; Focusing; Hyperspectral imaging; Machine learning; Pattern recognition; Pervasive computing; Pixel; Spatial databases;

fLanguage

English

Journal_Title

Computational Intelligence Magazine, IEEE

Publisher

ieee

ISSN

1556-603X

Type

jour

DOI

10.1109/MCI.2010.936311

Filename

5447954