A comparative study of improvements Pre-filter methods bring on feature selection using microarray data.

ABSTRACT:

Background

Feature selection techniques have become an apparent need in biomarker discoveries with the development of microarray. However, the high dimensional nature of microarray made feature selection become time-consuming. To overcome such difficulties, filter data according to the background knowledge before applying feature selection techniques has become a hot topic in microarray analysis. Different methods may affect final results greatly, thus it is important to evaluate these pre-filter methods in a system way.

Methods

In this paper, we compared the performance of statistical-based, biological-based pre-filter methods and the combination of them on microRNA-mRNA parallel expression profiles using L1 logistic regression as feature selection techniques. Four types of

SUBMITTER: Wang Y 

PROVIDER: S-EPMC4340279 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature