'Logistic regression' vs. 'multiple linear regression' - Is the answer in the exam preparedness test wrong?

Question

Hi,

I answered the 50 questions that test one's readiness to take the exam for the Azure AI Fundamentals AI-900 certification.

I think that the answer to one question is wrong.

In the answers, one can find the explanation that 'multiple linear regression models a relationship between two or more features and a single label'. The question which machine learning model should be chosen relates to establishing the relation between body fat, age and the risk of diabetes. Thus, there are two features and one label. Consequently, 'multiple linear regression' seems to be to be the correct answer to me.

Yet, this answer is marked as wrong and 'logistic regression' is marked as correct (see screenshot).

Am I right assuming that this is an error and that 'multiple linear regression' should be marked as the correct answer?

If yes, I would like to know before I take the exam. Moreover, I would suggest to correct the exam preparedness test accordingly.

Answer 1

yep - agreed. As a matter of fact, there is almost identical example at https://learn.microsoft.com/ms-my/training/modules/understand-regression-machine-learning/4-multiple-linear-regression

It's worth noting thought that rather than modeling a single relationship, this technique simultaneously models multiple relationships, which it treats as independent of one another. This nuance seems to be missing from the question.

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hth

Marcin

Answer 2

Thanks for reaching out to us, I am sorry to see this confused information, but I would like you to post the question to the right forum so that you can double check with the exam prep team.

The right forum are below -

Microsoft Learning https://techcommunity.microsoft.com/t5/microsoft-learn/ct-p/MicrosoftLearn

Microsoft Exams - Exam Prep Resources https://trainingsupport.microsoft.com/en-us/mcp/forum/mcp_exams-mcp_prep

I hope this helps!

Regards,

Yutong

-Please kindly accept the answer if you feel helpful to support the community, thanks a lot.