Team 7 presented their findings on anomaly detection in credit card transactions. They tested several techniques including random forests with SMOTE oversampling, one class SVMs, and threshold tuning to optimize AUC. Their best model predicted 98% of fraud transactions while maintaining high precision and recall. They demonstrated their model on a live credit card fraud detection system and for analyzing single transactions.
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