2003 · 84 citations · 37 references
Software MaintenanceEngineeringBusiness IntelligenceSoftware EngineeringBusiness AnalyticsWeb AnalyticsSoftware AnalysisEmpirical Software Engineering ResearchInformation RetrievalData ScienceData MiningWeb Hypermedia ApplicationsManagementSoftware Engineering EconomicsStatisticsWeb EngineeringSoftware EconomicsCase-based ReasoningSoftware MeasurementPredictive AnalyticsKnowledge DiscoveryWeb TrendSoftware DesignEffort PredictionWeb MiningWeb PerformanceProgram AnalysisWeb IntelligenceSoftware TestingStepwise Regression
Several studies have compared the prediction accuracy of different types of techniques with emphasis placed on linear and stepwise regressions, and case-based reasoning (CBR). We believe the use of only one type of CBR technique may bias the results, as there are others that can also be used for effort prediction. This paper has two objectives. The first is to compare the prediction accuracy of three CBR techniques to estimate the effort to develop Web hypermedia applications. The second objective is to compare the prediction accuracy of the best CBR technique, according to our findings, against three commonly used prediction models, namely multiple linear regression, stepwise regression and regression trees. One dataset was used in the estimation process and the results showed that different measures of prediction accuracy gave different results. MMRE and MdMRE showed better prediction accuracy for multiple regression models whereas box plots showed better accuracy for CBR.
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Classification and Regression Trees.
John Van Ryzin, Leo Breiman, Jerome H. Friedman et al. · Journal of the American Statistical Association · 1986 · 21K citations
Classification and regression trees
J. Praagman · European Journal of Operational Research · 1985 · 10.2K citations