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

Šilhavý, Petr; Šilhavý, Radek; Prokopová, Zdenka

Title:	Evaluation of data clustering for stepwise linear regression on use case points estimation
Author:	Šilhavý, Petr; Šilhavý, Radek; Prokopová, Zdenka
Document type:	Conference paper (English)
Source document:	Advances in Intelligent Systems and Computing. 2017, vol. 575, p. 491-496
ISSN:	2194-5357 (Sherpa/RoMEO, JCR)

ISBN:	978-3-319-57140-9
DOI:	https://doi.org/10.1007/978-3-319-57141-6_52
Abstract:	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. © Springer International Publishing AG 2017.
Full text:	https://link.springer.com/chapter/10.1007/978-3-319-57141-6_52
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Citace článku v konferenčním sborníku:
ŠILHAVÝ, Petr, Radek ŠILHAVÝ a Zdenka PROKOPOVÁ. Evaluation of data clustering for stepwise linear regression on use case points estimation. In: Advances in Intelligent Systems and Computing [online]. Springer Verlag, 2017, s. 491-496. [cit. 2024-11-22]. ISSN 2194-5357. Dostupné z: https://link.springer.com/chapter/10.1007/978-3-319-57141-6_52.

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