DocumentCode :
1093999
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
Volume :
33
Issue :
9
fYear :
2007
Firstpage :
637
Lastpage :
640
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;
fLanguage :
English
Journal_Title :
Software Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0098-5589
Type :
jour
DOI :
10.1109/TSE.2007.70721
Filename :
4288197
Link To Document :
بازگشت