Further thoughts on precision

Gray, D. and Bowes, D. and Davey, N. and Sun, Y. and Christianson, B. (2011) Further thoughts on precision. In: 15th Annual Conference on Evaluation & Assessment in Software Engineering (EASE 2011). IEEE, pp. 129-133. ISBN 9781849195096

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Background: There has been much discussion amongst automated software defect prediction researchers regarding use of the precision and false positive rate classifier performance metrics. Aim: To demonstrate and explain why failing to report precision when using data with highly imbalanced class distributions may provide an overly optimistic view of classifier performance. Method: Well documented examples of how dependent class distribution affects the suitability of performance measures. Conclusions: When using data where the minority class represents less than around 5 to 10 percent of data points in total, failing to report precision may be a critical mistake. Furthermore, deriving the precision values omitted from studies can reveal valuable insight into true classifier performance.

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18 Mar 2019 11:00
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15 Sep 2023 02:01