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Please use this identifier to cite or link to this item: http://hdl.handle.net/10481/32916

Title: An extension on "statistical comparisons of classifiers over multiple data sets" for all pairwise comparisons
Authors: García, Salvador
Herrera, Francisco
Issue Date: 2008
Abstract: In a recently published paper in JMLR, Demsar (2006) recommends a set of non-parametric statistical tests and procedures which can be safely used for comparing the performance of classifiers over multiple data sets. After studying the paper, we realize that the paper correctly introduces the basic procedures and some of the most advanced ones when comparing a control method. However, it does not deal with some advanced topics in depth. Regarding these topics, we focus on more powerful proposals of statistical procedures for comparing n*n classifiers. Moreover, we illustrate an easy way of obtaining adjusted and comparable p-values in multiple comparison procedures.
Sponsorship: This research has been supported by the project TIN2005-08386-C05-01. S. García holds a FPU scholarship from Spanish Ministry of Education and Science.
Publisher: MIT Press
Keywords: Statistical methods
Non-parametric test
Multiple comparison tests
Adjusted p-values
Logically related hypotheses
URI: http://hdl.handle.net/10481/32916
ISSN: 1532-4435
Rights : Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License
Citation: García, S.; Herrera, F. An extension on "statistical comparisons of classifiers over multiple data sets" for all pairwise comparisons. Journal of Machine Learning Research, 9: 2677-2694 (2008). [http://hdl.handle.net/10481/32916]
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