Exclude specific model families from the candidate pool and Block selected feature transformations and encodings are correct.

With Exclude specific model families from the candidate pool you can narrow the set of algorithms AutoML considers so you can enforce constraints such as interpretability requirements or latency budgets and guide the search toward acceptable model types.

Using Block selected feature transformations and encodings lets you prevent AutoML from applying particular preprocessing steps so you retain control over feature engineering and ensure only allowed transformations and encodings are used.

Override the automatic choice of the primary evaluation metric is incorrect because the primary metric is explicitly configured for the AutoML experiment rather than being something you override mid run, so metric selection is handled at configuration time not by overriding an internal automatic choice.

Disable scaling and normalization of numeric inputs is incorrect because AutoML does not offer a single global toggle to simply turn off numeric scaling. Instead you manage preprocessing by blocking specific transformations and encodings as noted in the correct option.

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