Spectral Clustering and Feature Selection for Microarray Data

被引：3
|
作者：
Garcia-Garcia, Dario [1 ]
Santos-Rodriguez, Raul [1 ]
机构：
[1] Univ Carlos III Madrid, Dept Signal Theory & Commun, Leganes, Spain
来源：
EIGHTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, PROCEEDINGS | 2009年
关键词：
MUTUAL INFORMATION;
D O I：
10.1109/ICMLA.2009.86
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Microarray datasets comprise a large number of gene expression values and a relatively small number of samples. Feature selection algorithms are very useful in these situations in order to find a compact subset of informative features. We propose a redundancy control method for algorithms in the recently proposed SPEC family of spectral-based feature selection algorithms. This method is applied to find relevant genes in order to cluster samples corresponding to three kinds of cancer: lung, breast and colon.
引用
收藏
页码：425 / 428
页数：4
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