On the assessment of software defect prediction models via ROC curves
نویسندگان
چکیده
منابع مشابه
Model Assessment with ROC Curves
Introduction Classification models and in particular binary classification models are ubiquitous in many branches of science and business. Consider, for example, classification models in bioinformatics that classify catalytic protein structures as being in an active or inactive conformation. As an example from the field of medical informatics we might consider a classification model that, given...
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Many organizations want to predict the number of defects (faults) in software systems, before they are deployed, to gauge the likely delivered quality and maintenance effort. To help in this, numerous software metrics and statistical models have been developed, with a correspondingly large literature. We provide a critical review of this literature and the state-of-the-art. Most of the wide ran...
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In constructing predictive models, investigators frequently assess the incremental value of a predictive marker by comparing the ROC curve generated from the predictive model including the new marker with the ROC curve from the model excluding the new marker. Many commentators have noticed empirically that a test of the two ROC areas often produces a non-significant result when a corresponding ...
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ژورنال
عنوان ژورنال: Empirical Software Engineering
سال: 2020
ISSN: 1382-3256,1573-7616
DOI: 10.1007/s10664-020-09861-4