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@InProceedings{Christensen:2006:CEC, author = "Steffen Christensen and Franz Oppacher", title = "The Y-Test: Fairly Comparing Experimental Setups with Unequal Effort", booktitle = "Proceedings of the 2006 IEEE Congress on Evolutionary Computation", year = "2006", editor = "Gary G. Yen and Lipo Wang and Piero Bonissone and Simon M. Lucas", pages = "1060--1065", address = "Vancouver", month = "6-21 " # jul, publisher = "IEEE Press", keywords = "genetic algorithms, genetic programming", ISBN = "0-7803-9487-9", DOI = "doi:10.1109/CEC.2006.1688330", size = "6 pages", abstract = "Evolutionary Computation has been dogged by a central statistical issue: how does one fairly compare the performance of two techniques which differ in the amount of work required? While Koza's computational effort statistic attempts to answer this problem, it is a point statistic and has other statistical problems. We present the y-test, a statistical test which takes as input a set of outcomes from the observed runs of two processes A and B. The y-test synthetically performs a work-balanced comparison between k runs of A and l runs of B. We show that by choosing k and l appropriately, we can compensate for the fact that one of the processes is computationally more efficient than the other.", notes = "WCCI 2006 - A joint meeting of the IEEE, the EPS, and the IEE. IEEE Catalog Number: 06TH8846D IEEE Xplore gives pages = {"}356--361{"},", }

Genetic Programming entries for Steffen Christensen Franz Oppacher