A feature selection method using improved regularized linear discriminant analysis

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Sharma, Alok
Paliwal, Kuldip K
Imoto, Seiya
Miyano, Satoru
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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.

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Machine Vision and Applications

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25

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3

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© 2013 Springer Berlin Heidelberg. This is an electronic version of an article published in Machine Vision and Applications, April 2014, Volume 25, Issue 3, pp 775-786. Machine Vision and Applications is available online at: http://link.springer.com/ with the open URL of your article.

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Theory of computation

Cognitive and computational psychology

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