Machine learning (ML) and data mining have established several effective applications in gene selection analysis. This paper review of machine learning supervised algorithms of gene selection. The high dimension that mean select a gene technique before submitting data to classifier. Supervised learning is learning involves an expert well-versed in the environment. We present a number of methods using machine learning supervised algorithms of gene selection data set leukaemia, colon, lymphoma. Furthermore, compare which algorithms is the best for using gene selection. Finding the accuracy of data set selection. The classification accuracy with minimum number of genes is improved better than further filtering and combination