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Model Testing

concept · part of Machine Learning & Data

Model testing is the process of evaluating a machine learning model's performance, robustness, and reliability before deployment.

Inside Model Testing (6)

• Test case design — Test case design for AI/ML systems ensures models behave correctly across a wide range of situations.
• Automated testing — Automating test execution ensures that every time a model is updated, test cases run in the background to check for issues.
• Continuous testing and monitoring — Testing is not a one-time activity.
• Edge-case testing — Testing a model with extreme values, missing data, out-of-distribution samples, and empty input to ensure graceful degradation.
• Load testing — Simulating high concurrent request volume to test a model's scalability under stress.
• Test case — A test case is a safety net for machine learning models, ensuring they perform not only in ideal conditions but also in real-world, unpredictable scenarios.

Connections

• Uses Edge-case testing
• Uses Load testing
• Related to Edge-case testing
• Related to Load testing

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