Title :
Problems with Precision: A Response to "Comments on \´Data Mining Static Code Attributes to Learn Defect Predictors\´"
Author :
Menzies, Tim ; Dekhtyar, Alex ; Distefano, Justin ; Greenwald, Jeremy
Author_Institution :
Dept. of Comput. Sci. & Electr. Eng., West Virginia Univ., Morgantown, WV
Abstract :
Zhang and Zhang argue that predictors are useless unless they have high precison&recall. We have a different view, for two reasons. First, for SE data sets with large neg/pos ratios, it is often required to lower precision to achieve higher recall. Second, there are many domains where low precision detectors are useful.
Keywords :
data mining; data mining static code attributes; defect predictors; Accuracy; Data mining; Detectors; Equations; NASA; Performance evaluation; Predictive models; Project management; Software engineering; Testing;
Journal_Title :
Software Engineering, IEEE Transactions on
DOI :
10.1109/TSE.2007.70721