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EASE 2011 : 15th Annual Conference on Evaluation & Assessment in Software Engineering : 11-12 April 2011.
- Format:
- Book
- Author/Creator:
- Institution of Engineering and Technology, issuing body, author.
- Language:
- English
- Subjects (All):
- Software engineering--Congresses.
- Software engineering.
- Physical Description:
- 1 online resource (168 pages)
- Place of Publication:
- Stevenage, England : IET, 2011.
- Summary:
- 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.
- Notes:
- Description based on: online resource; title from title screen (IEEE Xplore Digital Library, viewed February 27, 2018).
- ISBN:
- 1-84919-509-9
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