Evaluating Defect Prediction using a Massive Set of Metrics
To evaluate the performance of a within-project defect prediction approach, people normally use precision, recall, and F-measure scores. However, in machine learning literature, there are a large number of evaluation metrics to evaluate the performance of an algorithm, (e.g., Matthews Correlation Co...
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Main Authors: | , , , |
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Format: | text |
Language: | English |
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Institutional Knowledge at Singapore Management University
2015
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Online Access: | https://ink.library.smu.edu.sg/sis_research/3081 https://ink.library.smu.edu.sg/context/sis_research/article/4081/viewcontent/Defect_prediction_metrics_xuan_2015_afv.pdf |
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Institution: | Singapore Management University |
Language: | English |