To reduce the false positive rate in fraud detection:

Adjust the Decision Threshold: Instead of the default 0.5, optimize it based on the ROC/PR curve. Use Weighted Loss Functions: Penalize false positives more heavily. Try a More Robust Model: XGBoost, Random Forest, or Anomaly Detection methods may improve performance. Apply Post-Processing: Reevaluate fraud cases with low confidence scores. For a detailed explanation: https://youtube.com/shorts/FfL_IwPWZqE?si=dSjN6eOgHNKG1Y3x 🚀