Model Selection and AutoML: Hyperparameters, Cross-Validation, the AutoML API and Feature Importance
Hyperparameter search and AutoML speed up model selection when the metric is right and the data has no leakage, but they cannot strengthen a weak signal. On Bookstore's cancellation risk we compare grid and random search for FastTree with cross-validation, the ML.NET AutoML API and the mlnet CLI that searches by accuracy, and show with real output how a leaky column produces an AUC of 1.0, Permutation Feature Importance and a fairness check by age and district.
15 Nov 2026
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15 min
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10
