DY0-001 · Question #31
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…
The correct answer is D. Running this model 100 times within a factory it is expected the model will predict error 90 out of. A confidence score of 0.90 is a probabilistic estimate, interpreted as the model assigning a 90% chance of an error on that particular factory instance, which in the long run corresponds to predicting "error" in about 90 out of every 100 identical runs.
Question
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?
Options
- ARunning this model for all known factory issues, it is expected the model will identify 90 out of 100
- BRunning this model on 100 samples of factories, a certain model performance is expected for 90
- CRunning this model 100 times on a factory, it is expected the model will predict 90 out of 100
- DRunning this model 100 times within a factory it is expected the model will predict error 90 out of
How the community answered
(39 responses)- A3% (1)
- B8% (3)
- C5% (2)
- D85% (33)
Explanation
A confidence score of 0.90 is a probabilistic estimate, interpreted as the model assigning a 90% chance of an error on that particular factory instance, which in the long run corresponds to predicting "error" in about 90 out of every 100 identical runs.
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