Finding conclusion stability for selecting the best effort predictor in software effort estimation

作者:Jacky Keung, Ekrem Kocaguneli, Tim Menzies

摘要

Background: Conclusion Instability in software effort estimation (SEE) refers to the inconsistent results produced by a diversity of predictors using different datasets. This is largely due to the “ranking instability” problem, which is highly related to the evaluation criteria and the subset of the data being used.

论文关键词:Effort estimation, Data mining, Stability, Linear regression, Regression trees, Neural nets, Analogy, MMRE, Evaluation criteria

论文评审过程:

论文官网地址:https://doi.org/10.1007/s10515-012-0108-5