Configure Liquid Neural Network parameters and event definitions for fraud detection
Configure the core parameters that control how the LNN learns and adapts to fraud patterns
Controls how quickly the model adapts to new data
Number of historical events to remember
Minimum confidence score to trigger fraud alert
Number of events to analyze in each batch
How quickly the model adjusts to changing patterns
Define the structure of events that will be processed by the fraud detection system
Payment transaction events from payment gateways
User authentication attempts
General account activity and changes
Current status of the ML configuration system
Configuration Active
ML system is running
5 Parameters
Configured and optimized
3 Event Types
Defined and monitored