Adding an 'overlap' class label for boundary majority points during generative model training improves synthetic minority data quality and downstream classifier accuracy on imbalanced tabular data.
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Synthetic Tabular Data Generation for Imbalanced Classification: The Surprising Effectiveness of an Overlap Class
Adding an 'overlap' class label for boundary majority points during generative model training improves synthetic minority data quality and downstream classifier accuracy on imbalanced tabular data.