Amazon MLS-C01 Exam - Topic 9 Question 36 Discussion

Actual exam question for Amazon's MLS-C01 exam

Question #: 36
Topic #: 9

A Machine Learning Specialist is working for a credit card processing company and receives an unbalanced dataset containing credit card transactions. It contains 99,000 valid transactions and 1,000 fraudulent transactions The Specialist is asked to score a model that was run against the dataset The Specialist has been advised that identifying valid transactions is equally as important as identifying fraudulent transactions

What metric is BEST suited to score the model?

APrecision

BRecall

CArea Under the ROC Curve (AUC)

DRoot Mean Square Error (RMSE)

Show Suggested Answer

Suggested Answer: A

by Rima at May 03, 2022, 07:45 PM

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Monroe

4 months ago

Surprised they didn't mention F1 score for balance!

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Bettye

5 months ago

Wait, isn't RMSE more for regression problems?

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Long

5 months ago

Definitely Recall, we need to catch those frauds!

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Gerald

5 months ago

I think Precision is more important here.

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Celeste

5 months ago

AUC is great for unbalanced datasets!

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Celeste

5 months ago

I remember learning about the different types of analytics in class. I think the key here is that descriptive analytics summarize what has happened, while the other types try to explain why, predict what will happen, or recommend actions. So I'll go with A, descriptive.

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Shawna

5 months ago

Hmm, the DMAIC model - I remember learning about that in class. Let me think this through carefully.

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Jenifer

5 months ago

Hmm, I'm not sure about this one. I'll need to review the Azure Virtual Desktop documentation again to make sure I understand the diagnostic settings requirements.

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