An empirical study to investigate oversampling methods for improving software defect prediction using imbalanced data

Research article (Neurocomputing, 2019) · cited 134× · AI/ML
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An empirical study to investigate oversampling methods for improving software defect prediction using imbalanced data

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An empirical study to investigate oversampling methods for improving software defect prediction using imbalanced data is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). An empirical study to investigate oversampling methods for improving software defect prediction using imbalanced data. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-empirical-study-to-investigate-oversampling-methods-for-improving-software-defect-prediction-using-imbalanced-data
MLA “An empirical study to investigate oversampling methods for improving software defect prediction using imbalanced data.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-empirical-study-to-investigate-oversampling-methods-for-improving-software-defect-prediction-using-imbalanced-data.
BibTeX @misc{4ortxyz_an-empirical-study-to-investigate-oversampling-methods-for-improving-software-defect-prediction-using-imbalanced-data_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An empirical study to investigate oversampling methods for improving software defect prediction using imbalanced data}}, year = {2026}, url = {https://4ort.xyz/entity/an-empirical-study-to-investigate-oversampling-methods-for-improving-software-defect-prediction-using-imbalanced-data}, note = {Accessed: 2026-05-24}}
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