A Comparative Study on Linear Combination Rules for Ensemble Effort Estimation

S. Amasaki
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引用次数: 2

Abstract

Context: Software effort estimation is a critical factor for project success. A new approach called ensemble effort estimation gets popular because of its performance. While many combination rules have been proposed, they were only compared in a systematic literature review. Objective: To compare linear combination rules proposed in the past studies under the same condition based on empirical approach. Method: We conducted an experiment with 9 linear combination rules, 7 datasets, and 4 effort estimation models. Results: We found 6 out of 9 linear combination rules never underperformed its base learners. No linear combination rule was superior to the others. Conclusion: No definitive rule was found while some linear combination rules can give competitive or better estimates than its base learners.
集成努力估计中线性组合规则的比较研究
背景:软件工作量评估是项目成功的关键因素。一种称为集成工作量估计的新方法因其性能而受到欢迎。虽然已经提出了许多组合规则,但它们仅在系统的文献综述中进行了比较。目的:以实证方法比较以往研究中提出的相同条件下的线性组合规则。方法:采用9条线性组合规则、7个数据集、4个工作量估算模型进行实验。结果:我们发现9个线性组合规则中有6个从未表现不佳。无线性组合规则优于其他规则。结论:没有明确的规则,而一些线性组合规则可以提供竞争或更好的估计比它的基础学习器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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