Diagnose train and validation error
Problem
Model A has training error and validation error. Model B has training error and validation error. Diagnose the dominant issue for each, explain the bias-variance tradeoff, and say which split may be used for final unbiased reporting.
Reveal answer or reference solution
A shows high variance/overfitting. B has more bias but a smaller generalization gap. Validation data selects models; the untouched test split is used once for final reporting. Increasing complexity usually lowers training bias but can increase variance.
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