EmDT combines UMAP clustering with a Transformer-based diffusion process to create synthetic fraud samples that improve XGBoost classification on credit card fraud data while preserving correlations and privacy.
Imbalanced-learn: A python toolbox to tackle the curse of imbalanced datasets in machine learning.Journal of machine learning research, 18(17):1–5, 2017
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EmDT: Embedding Diffusion Transformer for Tabular Data Generation in Fraud Detection
EmDT combines UMAP clustering with a Transformer-based diffusion process to create synthetic fraud samples that improve XGBoost classification on credit card fraud data while preserving correlations and privacy.