Neural network based software effort estimation & evaluation criterion MMRE

Vachik S. Dave, Kamlesh Dutta
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引用次数: 20

Abstract

Evaluation of any prediction model is the most important part for comparison. Mean Magnitude Relative Error (MMRE) is one of the traditional evaluation criterion. In this paper we demonstrate the application of MMRE for model for predicting software development effort estimation and show that MMRE is not a suitable evaluation criterion for the software development estimation models. The argument is supported by series of simulations. In this paper we also suggest changes needed in MMRE calculations and propose Modified MMRE algorithm for the effort estimation evaluation criterion.
基于神经网络的软件工作量估算与评价准则
任何预测模型的评价都是进行比较的最重要的部分。平均幅度相对误差(MMRE)是传统的评价标准之一。本文论证了MMRE在预测软件开发工作量估算模型中的应用,并指出MMRE并不是一个适合于软件开发估算模型的评估准则。这一论点得到了一系列模拟的支持。本文还提出了MMRE计算中需要改变的地方,并提出了改进的MMRE算法作为工作量估计评价准则。
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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