Yasutaka Kamei
Akito Monden
ABSTRACT
This paper proposes a novel method to generate synthetic projectcases and add them to a fit dataset for the purpose of improving the performance of analogy-based software effort estimation. The proposed method extends conventional over-sampling method, which is a preprocessing procedure for n-group classification problems, which makes it suitable for any imbalanced dataset to be used in analogy-based system. We experimentally evaluated the effect of the over-sampling method to improve the performance of the analogy-based software effort estimation by using the Desharnais dataset. Results show significant improvement to the estimation accuracy by using our approach.
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Cross Ref
- J. M. Desharnais. Analyse statistique de la productivitie des projets informatique a partie de la technique des point des fonction. Master's thesis, University of Montreal, 1989.Google Scholar
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Index Terms
- An over-sampling method for analogy-based software effort estimation
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