A Meta-analytical Comparison of Naive Bayes and Random Forest for Software Defect Prediction
June 27, 2023 Β· Declared Dead Β· π International Conference on Intelligent Systems Design and Applications
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Authors
Ch Muhammad Awais, Wei Gu, Gcinizwe Dlamini, Zamira Kholmatova, Giancarlo Succi
arXiv ID
2306.15369
Category
cs.SE: Software Engineering
Cross-listed
cs.LG
Citations
3
Venue
International Conference on Intelligent Systems Design and Applications
Last Checked
4 months ago
Abstract
Is there a statistical difference between Naive Bayes and Random Forest in terms of recall, f-measure, and precision for predicting software defects? By utilizing systematic literature review and meta-analysis, we are answering this question. We conducted a systematic literature review by establishing criteria to search and choose papers, resulting in five studies. After that, using the meta-data and forest-plots of five chosen papers, we conducted a meta-analysis to compare the two models. The results have shown that there is no significant statistical evidence that Naive Bayes perform differently from Random Forest in terms of recall, f-measure, and precision.
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