PMI CPMAI_v7 Exam - 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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Lashanda

2 months ago

Neural Networks? Really? That seems overkill for a small dataset.

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Theron

2 months ago

I agree, Naive Bayes is a solid choice here.

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Vicente

3 months ago

Ensemble models might be too complex for this situation.

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Yuriko

3 months ago

Generative AI? I didn't think that was suitable for this kind of task!

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Alease

3 months ago

Naive Bayes is simple and works well with limited data!

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Mollie

3 months ago

Neural networks seem like overkill here, right? I feel like we should stick with something simpler.

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Kindra

4 months ago

I practiced a similar question, and I think Naive Bayes was mentioned as a good option for limited data.

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Marjory

4 months ago

I’m not entirely sure, but I think ensemble models might be too complex for this situation.

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Xenia

4 months ago

I remember we discussed that simpler models are often better for smaller datasets, so maybe Naive Bayes could be a good fit?

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Son

4 months ago

Okay, let me think this through step-by-step. The key factors are simplicity and limited data, so I'm going to go with Naive Bayes. It's a straightforward algorithm that can work well even with a small dataset. I feel pretty confident about this choice.

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Teri

4 months ago

Neural networks could be an interesting option here, but given the constraints, I'm not sure if that's the best approach. Generative AI is intriguing, but I don't think it's the right fit for this type of problem. I'm leaning towards Naive Bayes as the safest bet.

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Lashunda

5 months ago

I'm a bit torn on this one. Naive Bayes could work, but with a limited data set, I'm wondering if an ensemble model might be a better choice to improve the predictive power. I'll have to think this through carefully.

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Dominga

5 months ago

Hmm, this seems like a pretty straightforward customer repurchase prediction problem. I'd probably go with Naive Bayes since it's a simple but effective algorithm, and the project owner wants something not too complicated.

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Alyce

7 months ago

Naive Bayes is the clear winner. Unless the project owner is a mad scientist who wants to unleash a generative AI model on this poor customer data. Yikes!

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