Sciweavers

Share
BMCBI
2010

A multi-filter enhanced genetic ensemble system for gene selection and sample classification of microarray data

11 years 1 months ago
A multi-filter enhanced genetic ensemble system for gene selection and sample classification of microarray data
Background: Feature selection techniques are critical to the analysis of high dimensional datasets. This is especially true in gene selection from microarray data which are commonly with extremely high feature-to-sample ratio. In addition to the essential objectives such as to reduce data noise, to reduce data redundancy, to improve sample classification accuracy, and to improve model generalization property, feature selection also helps biologists to focus on the selected genes to further validate their biological hypotheses. Results: In this paper we describe an improved hybrid system for gene selection. It is based on a recently proposed genetic ensemble (GE) system. To enhance the generalization property of the selected genes or gene subsets and to overcome the overfitting problem of the GE system, we devised a mapping strategy to fuse the goodness information of each gene provided by multiple filtering algorithms. This information is then used for initialization and mutation oper...
Pengyi Yang, Bing Bing Zhou, Zili Zhang, Albert Y.
Added 08 Dec 2010
Updated 08 Dec 2010
Type Journal
Year 2010
Where BMCBI
Authors Pengyi Yang, Bing Bing Zhou, Zili Zhang, Albert Y. Zomaya
Comments (0)
books