ML Model Testing

Testing ML Models

Ensure model quality through testing.

Data Tests

Schema validation: expected features, types. Distribution tests: compare to baseline.

Label quality: correct labels, consistent.

Model Tests

Unit tests: individual functions. Integration tests: pipeline components.

Performance tests: meets accuracy threshold. Regression tests: no degradation from baseline.

A/B Testing

Compare models in production. Statistical significance. Business metrics.

Key Takeaways

1. Test data, model, performance
2. A/B tests compare models
3. Automated tests catch issues early