软件开发工作量估算的Encourage回归模型：比较研究
Ensemble Regression Models for Software Development Effort Estimation: A Comparative Study
摘要：
随着对计算机软件的需求不断增加，软件的范围和复杂性变得比以往任何时候都高。软件行业确实需要对正在开发的项目进行准确的评估。软件开发工作量估算是软件项目管理的主要过程之一。然而，高估和低估都可能导致软件产业的损失。这项研究确定了哪种技术具有更好的努力预测精度，并提出了组合技术，可以提供更好的估计。基于平均绝对残差（MAR）准则和统计检验，对8种不同的集成模型进行了比较。结果表明，所提出的集成模型，除了提供高效率相比，它的同行，并产生最佳的响应软件项目的努力估计。因此，在这项研究中提出的集成模型将有助于项目经理与开发质量的软件。
英文摘要：
As demand for computer software continually increases, software scope and complexity become higher than ever. The software industry is in real need of accurate estimates of the project under development. Software development effort estimation is one of the main processes in software project management. However, overestimation and underestimation may cause the software industry loses. This study determines which technique has better effort prediction accuracy and propose combined techniques that could provide better estimates. Eight different ensemble models to estimate effort with Ensemble Models were compared with each other base on the predictive accuracy on the Mean Absolute Residual (MAR) criterion and statistical tests. The results have indicated that the proposed ensemble models, besides delivering high efficiency in contrast to its counterparts, and produces the best responses for software project effort estimation. Therefore, the proposed ensemble models in this study will help the project managers working with development quality software.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
