dc.contributor.author Shepperd, M
dc.contributor.author MacDonell, SG
dc.date.accessioned 2012-06-13T23:10:52Z
dc.date.available 2012-06-13T23:10:52Z
dc.date.copyright 2012
dc.date.issued 2012-06-14
dc.identifier.citation Information and Software Technology, vol.54(8), pp.820 - 827
dc.identifier.uri http://hdl.handle.net/10292/4423
dc.description.abstract Context Software engineering has a problem in that when we empirically evaluate competing prediction systems we obtain conflicting results. Objective To reduce the inconsistency amongst validation study results and provide a more formal foundation to interpret results with a particular focus on continuous prediction systems. Method A new framework is proposed for evaluating competing prediction systems based upon (1) an unbiased statistic, Standardised Accuracy, (2) testing the result likelihood relative to the baseline technique of random ‘predictions’, that is guessing, and (3) calculation of effect sizes. Results Previously published empirical evaluations of prediction systems are re-examined and the original conclusions shown to be unsafe. Additionally, even the strongest results are shown to have no more than a medium effect size relative to random guessing. Conclusions Biased accuracy statistics such as MMRE are deprecated. By contrast this new empirical validation framework leads to meaningful results. Such steps will assist in performing future meta-analyses and in providing more robust and usable recommendations to practitioners.
dc.publisher Elsevier
dc.publisher AUT University
dc.relation.uri http://dx.doi.org/10.1016/j.infsof.2011.12.008
dc.rights Copyright © 2012 Elsevier Ltd. All rights reserved. This is the author’s version of a work that was accepted for publication in (see Citation). Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. The definitive version was published in (see Citation). The original publication is available at (see Publisher's Version).
dc.title Evaluating prediction systems in software project estimation
dc.type Journal Article
dc.rights.accessrights OpenAccess
dc.identifier.doi 10.1016/j.infsof.2011.12.008
aut.relation.endpage 827
aut.relation.issue 8
aut.relation.startpage 820
aut.relation.volume 54

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