A feature selection method using improved regularized linear discriminant analysis

Authors:
Alok Sharma;Kuldip K. Paliwal;Seiya Imoto;Satoru Miyano
Affiliations:
Laboratory of DNA Information Analysis, University of Tokyo, Tokyo, Japan and School of Engineering, Griffith University, Brisbane, Australia and School of Engineering and Physics, University of t ...;School of Engineering, Griffith University, Brisbane, Australia;Laboratory of DNA Information Analysis, University of Tokyo, Tokyo, Japan;Laboratory of DNA Information Analysis, University of Tokyo, Tokyo, Japan
Venue:
Machine Vision and Applications
Year:
2014

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Abstract

Investigation of genes, using data analysis and computer-based methods, has gained widespread attention in solving human cancer classification problem. DNA microarray gene expression datasets are readily utilized for this purpose. In this paper, we propose a feature selection method using improved regularized linear discriminant analysis technique to select important genes, crucial for human cancer classification problem. The experiment is conducted on several DNA microarray gene expression datasets and promising results are obtained when compared with several other existing feature selection methods.