Evaluating microarray-based classifiers: an overview

Cancer Inform. 2008;6:77-97. doi: 10.4137/cin.s408. Epub 2008 Feb 29.

Abstract

For the last eight years, microarray-based class prediction has been the subject of numerous publications in medicine, bioinformatics and statistics journals. However, in many articles, the assessment of classification accuracy is carried out using suboptimal procedures and is not paid much attention. In this paper, we carefully review various statistical aspects of classifier evaluation and validation from a practical point of view. The main topics addressed are accuracy measures, error rate estimation procedures, variable selection, choice of classifiers and validation strategy.

Keywords: accuracy measures; classification; conditional and unconditional error rate; error rate estimation; gene expression; high-dimensional data; validation data; variable selection.