A Deep Learning Ensemble With Data Resampling For Credit Card Fraud Detection
The proposed deep learning ensemble combined with the SMOTE-ENN method achieved a sensitivity of 1.000 and a specificity of 0.997.
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The proposed deep learning ensemble combined with the SMOTE-ENN method achieved a sensitivity of 1.000 and a specificity of 0.997.
The proposed hybrid AI system was trained and evaluated on a transaction dataset containing more than 6 million records with transaction time steps ranging from 0 to 743.