Abstract A.-L. Boulesteix¹, C. Strobl², T. Augustin² and M. Daumer¹

¹Sylvia Lawry Centre for MS Research (SLC), Hohenlindenerstr. 1, 81677 Munich, Germany. ²Department of Statistics, University of Munich (LMU), Ludwigstr. 33, 80539 Munich, Germany.

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.

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