An empirical study to investigate oversampling methods for improving software defect prediction using imbalanced data
Author:
Funder
Indiana University
Purdue University
Google
Publisher
Elsevier BV
Subject
Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications
Reference69 articles.
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3. Toward comprehensible software fault prediction models using bayesian network classifiers;Dejaeger;IEEE Trans. Softw. Eng.,2013
4. Semi-supervised software defect prediction using task-driven dictionary learning;Cheng;Chin. J. Electron.,2016
5. An empirical comparison of model validation techniques for defect prediction models;Tantithamthavorn;IEEE Trans. Softw. Eng.,2017
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