DD-EbA：一种通过使用距离分布进行类比来确定成本估计中邻居数量的算法
DD-EbA: An algorithm for determining the number of neighbors in cost estimation by analogy using distance distributions
摘要：
基于案例的推理，特别是类比估算，已被用于许多问题解决领域，如成本估算。传统的方法，尽管缺乏一个健全的标准来选择最近的项目，是基于估计使用一个固定的和预定数量的邻居从整个历史实例集。这种方法限制了这种算法的估计能力，因为它们没有考虑到每个被估计的项目都是唯一的，需要不同的处理。距离分布的概念与分布的距离度量一起帮助我们每次将所提出的方法（我们称之为DD-EbA）适应于要估计的特定情况，而不会损失预测能力或计算成本。本文的结果表明，所提出的技术实现了上述想法在一个非常有效的方式。
英文摘要：
Case Based Reasoning and particularly Estimation by Analogy, has been used in a number of problem-solving areas, such as cost estimation. Conventional methods, despite the lack of a sound criterion for choosing nearest projects, were based on estimation using a fixed and predetermined number of neighbors from the entire set of historical instances. This approach puts boundaries to the estimation ability of such algorithms, for they do not take into consideration that every project under estimation is unique and requires different handling. The notion of distributions of distances together with a distance metric for distributions help us to adapt the proposed method (we call it DD-EbA) each time to a specific case that is to be estimated without loosing in prediction power or computational cost. The results of this paper show that the proposed technique achieves the above idea in a very efficient way.
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。
