Databricks Exam Databricks-Certified-Professional-Data-Scientist Topic 4 Question 37 Discussion

Actual exam question for Databricks's Databricks-Certified-Professional-Data-Scientist exam

Question #: 37
Topic #: 4

[All Databricks-Certified-Professional-Data-Scientist Questions]

RMSE is a good measure of accuracy, but only to compare forecasting errors of different models for a______, as it is scale-dependent.

ABetween Variables

BParticular Variable

CAmong all the variables

DAll of the above are correct

Show Suggested Answer

Suggested Answer: C

by Roosevelt at Feb 07, 2023, 02:40 PM

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Aleta

14 days ago

I'm going to have to go with B) Particular Variable. RMSE is like a ruler - it only works if you're measuring the same thing. Trying to use it across different variables is like measuring your height with a banana, am I right?

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Tracey

15 days ago

Hmm, this is a tough one. I'm leaning towards C) Among all the variables, but I'm not entirely sure. RMSE must be a pretty important metric if it's on this exam.

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Joaquin

17 days ago

I'm going with A) Between Variables. RMSE is a great way to compare model performance, even if the variables have different scales. Maybe I'll get lucky!

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Wilda

5 hours ago

I agree, RMSE is a useful tool for comparing forecasting errors across different models.

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Tiffiny

2 days ago

I think A) Between Variables is the right choice too. It's important to consider scale when comparing models.

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Heike

18 days ago

D) All of the above are correct seems like the safest choice. RMSE can be used to compare models across variables, as long as they are on the same scale.

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Oneida

20 days ago

I think the correct answer is B) Particular Variable. RMSE is used to compare the forecasting errors of different models for the same variable, not across different variables.

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