Performance validation of microarray analysis methods Performance validation of microarray analysis methods Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2015-10-262008enFollowing the rapid development of gene selection methods, several comparison studies have been reported for ranking methods on various datasets. In order to reduce bias in performance measures, most studies use an evaluation scheme based on cross-validation. In this paper we focus on the methodology of evaluation itself and address methodological problems using three representative algorithms on two public datasets. More specifically, the paper discusses the need of an independent test-set to reduce bias associated with cross-validation, the use of case specific considerations for generalization, as well as other measures that reflect stability and consistency of the result. Such measures reflect the influence of the actual dataset distribution on the performance of gene selection methods.http://creativecommons.org/licenses/by/4.0/1-68th IEEE International Conference on BioInformatics and BioEngineering Danilatou Vasiliki Kafetzopoulos Dimitris Tsiknakis Manolis Blazadonakis Michalis E. Zervakis Michail Ζερβακης Μιχαηλ Banti Anna Institute of Electrical and Electronics Engineers Performance analysis Filters Cancer Biomedical measurements Genomics Bioinformatics Stability Humans System testing Decision support systems