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dc.contributor.authorGray, Andrewen_NZ
dc.contributor.authorMacDonell, Stephenen_NZ
dc.date.available2011-04-07T03:05:21Z
dc.date.copyright1999-06en_NZ
dc.identifier.citationGray, A., & MacDonell, S. (1999). Software metrics data analysis—Exploring the relative performance of some commonly used modeling techniques (Information Science Discussion Papers Series No. 99/11). University of Otago. Retrieved from http://hdl.handle.net/10523/877en
dc.identifier.urihttp://hdl.handle.net/10523/877
dc.description.abstractWhilst some software measurement research has been unquestionably successful, other research has struggled to enable expected advances in project and process management. Contributing to this lack of advancement has been the incidence of inappropriate or non-optimal application of various model-building procedures. This obviously raises questions over the validity and reliability of any results obtained as well as the conclusions that may have been drawn regarding the appropriateness of the techniques in question. In this paper we investigate the influence of various data set characteristics and the purpose of analysis on the effectiveness of four model-building techniques---three statistical methods and one neural network method. In order to illustrate the impact of data set characteristics, three separate data sets, drawn from the literature, are used in this analysis. In terms of predictive accuracy, it is shown that no one modeling method is best in every case. Some consideration of the characteristics of data sets should therefore occur before analysis begins, so that the most appropriate modeling method is then used. Moreover, issues other than predictive accuracy may have a significant influence on the selection of model-building methods. These issues are also addressed here and a series of guidelines for selecting among and implementing these and other modeling techniques is discussed.en_NZ
dc.format.mimetypeapplication/pdf
dc.publisherUniversity of Otagoen_NZ
dc.relation.ispartofseriesInformation Science Discussion Papers Seriesen_NZ
dc.subjectsoftware metricsen_NZ
dc.subjectanalysisen_NZ
dc.subjectstatistical methodsen_NZ
dc.subjectconnectionist methodsen_NZ
dc.subject.lcshQA76 Computer softwareen_NZ
dc.titleSoftware metrics data analysis—Exploring the relative performance of some commonly used modeling techniquesen_NZ
dc.typeDiscussion Paperen_NZ
dc.description.versionUnpublisheden_NZ
otago.bitstream.pages22en_NZ
otago.date.accession2010-11-02 20:16:25en_NZ
otago.schoolInformation Scienceen_NZ
otago.openaccessOpen
otago.place.publicationDunedin, New Zealanden_NZ
dc.identifier.eprints995en_NZ
otago.school.eprintsSoftware Metrics Research Laboratoryen_NZ
otago.school.eprintsInformation Scienceen_NZ
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otago.relation.number99/11en_NZ
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