A data scientist has built a model that provides the likelihood of an error occurring...

→ A likelihood score of 0.90 indicates the model’s confidence that an error will occur in this particular instance. Interpreted probabilistically, it means that if this scenario happened 100 times, the model would expect an error in 90 of those cases.

Why the other options are incorrect:

A: Confuses confidence with recall or precision.

B: Refers to model sampling performance, not instance-level prediction.

C: Implies a prediction of actual factory errors — not the model’s forecast probability.

Official References:

CompTIA DataX (DY0-001) Study Guide – Section 3.2:“A confidence score in a classification model indicates the model’s belief in the outcome of a specific prediction.”

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