An Extension on "Statistical Comparisons of Classifiers over Multiple Data Sets" for all Pairwise Comparisons Export

@article{citeulike:3849197, abstract = {In a recently published paper in JMLR, Dem\&\#154;ar (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 \&\#215; n classifiers. Moreover, we illustrate an easy way of obtaining adjusted and comparable p-values in multiple comparison procedures.}, author = {Garc\&\#237;a, Salvador and Herrera, Francisco}, citeulike-article-id = {3849197}, citeulike-linkout-0 = {http://www.jmlr.org/papers/volume9/garcia08a/garcia08a.pdf}, journal = {Journal of Machine Learning Research}, keywords = {classifiers, learning}, month = {December}, pages = {2677--2694}, posted-at = {2009-01-15 14:54:33}, priority = {2}, title = {An Extension on "Statistical Comparisons of Classifiers over Multiple Data Sets" for all Pairwise Comparisons}, url = {http://www.jmlr.org/papers/volume9/garcia08a/garcia08a.pdf}, volume = {9}, year = {2008} }

TY - JOUR ID - citeulike:3849197 L3 - citeulike-article-id:3849197 N2 - In a recently published paper in JMLR, Demšar (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. JF - Journal of Machine Learning Research EP - 2694 TI - An Extension on "Statistical Comparisons of Classifiers over Multiple Data Sets" for all Pairwise Comparisons VL - 9 SP - 2677 KW - classifiers KW - learning AU - García, Salvador AU - Herrera, Francisco PY - 2008/12// UR - http://www.jmlr.org/papers/volume9/garcia08a/garcia08a.pdf ER -