Build and evaluate

Use these guides to configure FraudTwin, construct analysis-ready data, train and evaluate models, and compare later windows with a reproducible baseline.

• Configuration
• Data and evaluation workflows
• ML evaluation methodology
• Model lifecycle: from simulation to service
• Data, domain, and concept shift
• Drift and shift operations