Some comparisons of gene expression classifiers

Abstract

Numerous computational studies related to cancer have been published, but increasing prediction accuracy of molecular datasets remains a challenge. Here we present a comparison of prediction based on a feature selection method combined with machine learning, for microRNA-Seq (miRNA-Seq) and mRNA-Seq data. We have tested three different approaches: support vector machine, decision tree and k nearest neighbors, under two different feature selection methods: fisher feature selection and infinite feature selection.