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

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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.

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Silhavy, P., Silhavy, R., & Prokopova, Z. (2017). Evaluation of data clustering for stepwise linear regression on use case points estimation. In Advances in Intelligent Systems and Computing (Vol. 575, pp. 491–496). Springer Verlag. https://doi.org/10.1007/978-3-319-57141-6_52

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