Naïve Bayes guided Binary Firefly Algorithm for Gene Selection in Cancer Classification

Abstract

The bioinformatics research must deal with the analysis of the large volume of data. Disease classification deals with the identification of relevant genes in almost all gene expression analyses, where researchers attempt to select a minimum number of genes with exceptional performance. The gene selection process mainly selects significant genes related to the disease. This work aims to accomplish relevant genes from large volume of candidate genes that help to identify cancers. In the proposed work, Binary Firefly Algorithm (BFA) helps to identify related genes using the Naive Bayes classifier. Based on the experimental results, Naïve Bayes guided Binary Firefly Algorithm (NBBFA) provided high accuracy with fewer genes