articleTop 1% cited
A Comprehensive Analysis of Synthetic Minority Oversampling Technique (SMOTE) for handling class imbalance
Information Sciences · 2019 · Vol. 505 · pp. 32–64
Dina Elreedy✉(Cairo University)Amir F. Atiya(Cairo University)
Imbalanced Data Classification TechniquesElectricity Theft Detection TechniquesAdvanced Statistical Process MonitoringOversamplingComputer scienceEconomic shortageClass (philosophy)Data miningMachine learningPoint (geometry)Set (abstract data type)Artificial intelligenceMathematics
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References
Cost-sensitive boosting for classification of imbalanced data
Pattern Recognition · 2007 · 1,416 citations
An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics
Information Sciences · 2013 · 1,562 citations
Learning from class-imbalanced data: Review of methods and applications
Expert Systems with Applications · 2016 · 2,276 citations
Improving imbalanced learning through a heuristic oversampling method based on k-means and SMOTE
Information Sciences · 2018 · 1,130 citations
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