Adaptive bagging strategies to address concept drift and retain knowledge in fraud detection systems

Key Points

• Improved knowledge retention leads to more accurate fraud detection.
• The model effectively adapts to concept drift, with a 20% increase in detection rates.
• Assessment based on real-time transaction data and machine learning algorithms.
• Implications for robust fraud detection systems that must adapt to changing patterns.