Improved direct LDA and its application to DNA microarray gene expression data

The direct linear discriminant analysis (DLDA) technique is a well known technique for dimensionality reduction. It can overcome the small sample size problem. However, its performance is limited. In this paper we address its drawbacks and propose an improvement of the DLDA technique. The experiment is conducted on several DNA microarray gene expression datasets and the performance (in terms of classification accuracy) of the proposed improvement of the technique is reported at 91.1% which is very promising.

Research highlights
► The proposed method is improvement of DLDA method.
► It addresses the small sample size problem.
► The performance in terms of classification accuracy on DNA gene expression datasets is very encouraging.