Abstract
To construct a better multivariate regression model for software effort estimation, this paper proposes a method to select projects as a fit data from a given project data set based on estimation target's features. While regression models were often constructed from all available project data, this paper showed the necessity of fit data selection, and showed that the proposed method is one of the effective and systematic means to do the selection.
| Original language | English |
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| Title of host publication | ESEM'08 |
| Subtitle of host publication | Proceedings of the 2008 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement |
| Pages | 360-361 |
| Number of pages | 2 |
| DOIs | |
| Publication status | Published - 2008 |
| Event | 2nd International Symposium on Empirical Software Engineering and Measurement, ESEM 2008 - Kaiserslautern, Germany Duration: Oct 9 2008 → Oct 10 2008 |
Publication series
| Name | ESEM'08: Proceedings of the 2008 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement |
|---|
Other
| Other | 2nd International Symposium on Empirical Software Engineering and Measurement, ESEM 2008 |
|---|---|
| Country | Germany |
| City | Kaiserslautern |
| Period | 10/9/08 → 10/10/08 |
Keywords
- Effort estimation
- Multivariate regression
ASJC Scopus subject areas
- Computer Science Applications
- Software
- Electrical and Electronic Engineering
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Cite this
Toda, K., Monden, A., & Matsumoto, K. I. (2008). Fit data selection for software effort estimation models. In ESEM'08: Proceedings of the 2008 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement (pp. 360-361). (ESEM'08: Proceedings of the 2008 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement). https://doi.org/10.1145/1414004.1414084