E. Mendes, I. Watson, Chris Triggs, Nile Mosley, S. Counsell
{"title":"Web超媒体应用程序开发工作量估算技术的比较","authors":"E. Mendes, I. Watson, Chris Triggs, Nile Mosley, S. Counsell","doi":"10.1109/METRIC.2002.1011332","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":165815,"journal":{"name":"Proceedings Eighth IEEE Symposium on Software Metrics","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"95","resultStr":"{\"title\":\"A comparison of development effort estimation techniques for Web hypermedia applications\",\"authors\":\"E. Mendes, I. Watson, Chris Triggs, Nile Mosley, S. Counsell\",\"doi\":\"10.1109/METRIC.2002.1011332\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":165815,\"journal\":{\"name\":\"Proceedings Eighth IEEE Symposium on Software Metrics\",\"volume\":\"98 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"95\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Eighth IEEE Symposium on Software Metrics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/METRIC.2002.1011332\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Eighth IEEE Symposium on Software Metrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/METRIC.2002.1011332","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A comparison of development effort estimation techniques for Web hypermedia applications
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.