Gene extraction for cancer diagnosis by support vector machines—An improvement

摘要

Objective:To improve the performance of gene extraction for cancer diagnosis by recursive feature elimination with support vector machines (RFE-SVMs): A cancer diagnosis by using the DNA microarray data faces many challenges the most serious one being the presence of thousands of genes and only several dozens (at the best) of patient's samples. Thus, making any kind of classification in high-dimensional spaces from a limited number of data is both an extremely difficult and a prone to an error procedure. The improved RFE-SVMs is introduced and used here for an elimination of less relevant genes and just for a reduction of the overall number of genes used in a medical diagnostic.