Evaluation of data clustering for stepwise linear regression on use case points estimation

Citation data:

Advances in Intelligent Systems and Computing, ISSN: 2194-5357, Vol: 575, Page: 491-496

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Repository URL:
http://publikace.k.utb.cz/handle/10563/1007392; http://hdl.handle.net/10563/1007392
Šilhavý, Petr; Šilhavý, Radek; Prokopová, Zdenka
Springer Nature; Springer Verlag
Engineering; Computer Science; Clustering; Effort estimation; Parametric model; Stepwise linear regression; Use case points
conference paper description
In this paper, stepwise linear regression model in conjunction with clustering for effort estimation is investigated. Effect of clustering is compared to Use Case Points model. The 2 to 20 clusters were tested. As shown increasing a number of clusters brings lower prediction errors. More clusters lower a distance between clusters members, which allows to construct more capable stepwise linear regression model.