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Select model complexity
Tutor me on https://mlprep.iwase.dev/item/ml-screen-theory-advanced-complexity/. This is a screening item. If window.mlPrepAgent is available, read attempts for item ml-screen-theory-advanced-complexity before tutoring. Inspect my attempt, keep the item ID, and do not reveal the full answer first. After a real attempt, append its record with recorded_by agent, include agent_session_id when available, and read it back.Problem
Low-, medium-, and high-complexity models have training errors and validation errors . Choose a model, compute the validation-minus-training gaps, diagnose low and high complexity, and state the next use of test data.
Reveal answer or reference solution
The gaps are . Select the medium-complexity model because its validation error, , is lowest. The low-complexity model has high training and validation error, indicating underfitting or high bias. The high-complexity model has tiny training error but worse validation error and a large gap, indicating overfitting or high variance. After fixing all choices, evaluate the selected model once on untouched test data.
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