Improving the Accuracy of Gene Expression Profile Classification with Lorenz Curves and Gini Ratios

摘要: Microarrays are a new technology with great potential to provide accurate medical diagnostics, help find the right treatment for many diseases such as cancers, and detailed genome-wide molecular portrait of cellular states. In this chapter, we show how Lorenz Curves Gini Ratios can be modified improve accuracy gene expression profile classification. Experimental results different classification algorithms using additional techniques strategies improving principal component analysis, correlation-based feature subset selection, consistency evaluation technique task classifying lung adenocarcinomas from that our method more optimal genes than SAM.