Microsoft Exam AI-900 Topic 2 Question 75 Discussion

Actual exam question for Microsoft's AI-900 exam

Question #: 75
Topic #: 2

[All AI-900 Questions]

What should you do to reduce the number of false positives produced by a machine learning classification model?

AInclude test data in the training data.

BIncrease the number of training iterations.

CModify the threshold value in favor of false positives.

DModify the threshold value in favor of false negatives.

Show Suggested Answer

Suggested Answer: A

by Rory at Sep 18, 2024, 09:56 AM

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Janna

11 days ago

Hmm, I think D is the way to go. Modifying the threshold to favor false negatives sounds like a good strategy to me.

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Casie

19 days ago

Yes, but it's a trade-off. We need to find the right balance to reduce false positives without increasing false negatives too much.

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Virgina

27 days ago

I'm pretty sure the answer is B. Increasing the number of training iterations should help the model learn better and reduce false positives.

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Kyoko

8 days ago

I agree with you, increasing the number of training iterations can also help reduce false positives.

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Nu

11 days ago

I think the answer is C. Modifying the threshold value in favor of false positives should help reduce them.

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Gearldine

28 days ago

But wouldn't that increase the number of false positives?

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Casie

1 months ago

I think we should modify the threshold value in favor of false positives.

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