Databricks Exam Databricks Certified Professional Data Scientist Topic 5 Question 71 Discussion

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

Question #: 71
Topic #: 5

[All Databricks Certified Professional Data Scientist Questions]

You are working in an ecommerce organization, where you are designing and evaluating a recommender system, you need to select which of the following metric wilt always have the largest value?

ARoot Mean Square Error

BSum of Errors

CMean Absolute Error

DBoth land 2

EInformation is not good enough.

Show Suggested Answer

Suggested Answer: E

by Olive at Sep 15, 2024, 09:02 PM

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Veronique

2 days ago

I think MAE could be larger in some cases.

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Kassandra

8 days ago

RMSE usually has the largest value due to squaring errors.

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Sylvie

14 days ago

I’m leaning towards RMSE being the largest, but I wonder if there are cases where the Sum of Errors could be larger too.

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Rene

19 days ago

I practiced a similar question where we compared different error metrics, and I think MAE is usually smaller than RMSE.

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Rex

24 days ago

I think the Sum of Errors could also be quite large, especially if the errors are significant. This question feels tricky.

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Harris

1 month ago

I remember we discussed that RMSE tends to be larger because it squares the errors, but I'm not entirely sure if it always has the largest value.

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Coral

1 month ago

I think the key here is to consider how each metric behaves. MAE is likely to be the largest since it doesn't square the errors like RMSE does.

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Marg

1 month ago

I'm a bit confused on the differences between these metrics. I'll need to review my notes on recommender system evaluation to make sure I understand the implications of each one.

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Cristen

1 month ago

I'm leaning towards Mean Absolute Error (MAE) as the answer. It's a more robust metric that doesn't penalize outliers as heavily as RMSE.

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Raylene

1 month ago

Okay, let me see. I know that RMSE is sensitive to outliers, so that might not be the largest. Sum of errors could be negative, so that's probably not it either.

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Elza

1 month ago

Hmm, this is a tricky one. I'll need to think carefully about the properties of these different error metrics.

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Carey

1 month ago

Hmm, I'm not totally sure about this one. I'm thinking it might be option B - Marketing suspended leads, but I'm not 100% confident.

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Renea

1 year ago

I'm going with C. It just makes the most sense to me. Although, I do enjoy a good Root Mean Square Error every now and then. Keeps things spicy, you know?

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Nikita

12 months ago

I'm leaning towards A, but C does have its merits.

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Laurena

1 year ago

I see where you're coming from, but I still think C is the best option.

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Jaime

1 year ago

I prefer D, it covers a wider range of errors.

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Margret

1 year ago

I think C is the way to go too. It's a solid choice.

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Colette

1 year ago

E. Information is not good enough? Well, that's just lazy. Come on, we can do better than that!

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Marti

12 months ago

D) Both 1 and 2

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Carlene

12 months ago

C) Mean Absolute Error

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Jesusita

1 year ago

A) Root Mean Square Error

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Tish

1 year ago

D. Both 1 and 2? Really? That's a bit of a cop-out, isn't it?

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Luann

1 year ago

E) Information is not good enough.

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Izetta

1 year ago

C) Mean Absolute Error

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Casie

1 year ago

A) Root Mean Square Error

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Valentin

1 year ago

Hmm, I'm not sure about this one. I'll have to think it through carefully.

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Tom

1 year ago

Let's double check the calculations before making a decision.

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Krystina

1 year ago

I'm leaning towards D) Both 1 and 2.

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Rolland

1 year ago

I believe it's between A) and C) Mean Absolute Error.

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Rolande

1 year ago

I think the answer is A) Root Mean Square Error.

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Percy

1 year ago

I'm not sure, but I think C) Mean Absolute Error could also have a large value depending on the data.

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Catina

1 year ago

I agree with Hubert, RMSE is commonly used in recommender systems.

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Reynalda

1 year ago

I think the answer is C. Mean Absolute Error is always the largest value compared to the other options.

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Justa

1 year ago

Great, it's an important metric to consider when evaluating the performance of a recommender system.

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Chanel

1 year ago

Yes, that's correct. It measures the average magnitude of errors without considering their direction.

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Yesenia

1 year ago

I agree, Mean Absolute Error is always the largest value.

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Shantay

1 year ago

E) Information is not good enough.

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Lazaro

1 year ago

D) Both 1 and 2

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Tiera

1 year ago

C) Mean Absolute Error

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Ena

1 year ago

B) Sum of Errors

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Theodora

1 year ago

A) Root Mean Square Error

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Hubert

1 year ago

I think the answer is A) Root Mean Square Error.

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