CompTIA DataX (DY0-001) — Question 67

A data scientist has built a model that provides the likelihood of an error occurring in a factory. The historical accuracy of the model is 90%. At a specific factory, the model is reporting a likelihood score of 0.90. Which of the following explains a confidence score of 0.90?

Answer options

• A. Running this model for all known factory issues, it is expected the model will identify 90 out of 100 known factory issues.
• B. Running this model on 100 samples of factories, a certain model performance is expected for 90 out of the 100 samples.
• C. Running this model 100 times on a factory, it is expected the model will predict 90 out of 100 factory errors.
• D. Running this model 100 times within a factory, it is expected the model will predict error 90 out of 100 times the model is ran.

Correct answer: D

Explanation

The correct answer, D, accurately indicates that if the model is run 100 times in the same factory, it is expected to predict errors correctly 90 times. This aligns with the confidence score of 0.90, meaning the model's predictions are reliable 90% of the time in that specific scenario. The other options misinterpret the context of the confidence score, focusing on different aspects of model performance rather than the repeated execution of predictions.