PMI Exam CPMAI_v7 Topic 1 Question 2 Discussion

Actual exam question for PMI's CPMAI_v7 exam

Question #: 2
Topic #: 1

You want to create a model to figure out if a customer would be likely to repurchase a certain item. The project owner doesn't want you to create anything too complicated, and you have a limited data set to work with.

Which algorithm is the best choice given these constraints?

AEnsemble models

BNaive Bayes

CNeural Networks

DGenerative AI

Show Suggested Answer

Suggested Answer: B

by Arletta at Jun 14, 2025, 05:56 AM

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Jennifer

4 days ago

I would go with Ensemble models. They can handle different types of data and provide more accurate predictions.

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Percy

5 days ago

I'm feeling Naive Bayes too. It's like the easy-bake oven of machine learning algorithms. Perfect for this project's constraints.

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Lashaunda

11 days ago

I agree with My. Naive Bayes is simple and works well with limited data.

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Ammie

14 days ago

Naive Bayes is the way to go here. It's simple, fast, and works well with limited data. No need for all that complicated neural network stuff.

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Erick

1 days ago

B) Naive Bayes

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Wenona

5 days ago

A) Ensemble models

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My

20 days ago

I think Naive Bayes would be the best choice.

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