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cs.LG2022
ConvGeN: Convex space learning improves deep-generative oversampling for tabular imbalanced classification on smaller datasets
Kristian Schultz, Saptarshi Bej, Waldemar Hahn +3
Data is commonly stored in tabular format. Several fields of research are prone to small imbalanced tabular data. Supervised Machine Learning on such data is often difficult due to…
cs.LG2021★ 1 cited
A multi-schematic classifier-independent oversampling approach for imbalanced datasets
Saptarshi Bej, Kristian Schultz, Prashant Srivastava +2
Over 85 oversampling algorithms, mostly extensions of the SMOTE algorithm, have been built over the past two decades, to solve the problem of imbalanced datasets. However, it has b…