Amazon
MLS-C01 · Question #209
A data scientist is evaluating a GluonTS on Amazon SageMaker DeepAR model. The evaluation metrics on the test set indicate that the coverage score is 0.489 and 0.889 at the 0.5 and 0.9 quantiles…
The correct answer is D. The coverage scores indicate that the distributional forecast is correctly calibrated. These. https://ts.gluon.ai/stable/tutorials/forecasting/quick_start_tutorial.html
Modeling
Question
A data scientist is evaluating a GluonTS on Amazon SageMaker DeepAR model. The evaluation metrics on the test set indicate that the coverage score is 0.489 and 0.889 at the 0.5 and 0.9 quantiles, respectively. What can the data scientist reasonably conclude about the distributional forecast related to the test set?
Options
- AThe coverage scores indicate that the distributional forecast is poorly calibrated. These
- BThe coverage scores indicate that the distributional forecast is poorly calibrated. These
- CThe coverage scores indicate that the distributional forecast is correctly calibrated. These
- DThe coverage scores indicate that the distributional forecast is correctly calibrated. These
How the community answered
(53 responses)- A6% (3)
- B17% (9)
- C8% (4)
- D70% (37)
Explanation
https://ts.gluon.ai/stable/tutorials/forecasting/quick_start_tutorial.html
Topics
#Probabilistic Forecasting#Model Evaluation#Coverage Score#Model Calibration
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