A feature selection method using improved regularized linear discriminant analysis

作者：Sharma Alok^*; Paliwal Kuldip K; Imoto Seiya; Miyano Satoru

来源：Machine Vision and Applications, 2014, 25(3): 775-786.

DOI：10.1007/s00138-013-0577-y

• Linear discriminant analysis (LDA)
• Regularized LDA
• Feature/gene selection
• Classification accuracy

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.

• 出版日期2014-4