Microsoft Exam AI-900 Topic 5 Question 55 Discussion

Actual exam question for Microsoft's AI-900 exam

Question #: 55
Topic #: 5

You need to create a clustering model and evaluate the model by using Azure Machine Learning designer. What should you do?

ASplit the original dataset into a dataset for features and a dataset for labels. Use the features dataset for evaluation.

BSplit the original dataset into a dataset for training and a dataset for testing. Use the training dataset for evaluation.

CSplit the original dataset into a dataset for training and a dataset for testing. Use the testing dataset for evaluation.

DUse the original dataset for training and evaluation.

Show Suggested Answer

Suggested Answer: C

by Donte at Dec 08, 2023, 08:23 AM

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Arlette

4 days ago

Haha, yeah, using the original dataset for both training and evaluation would be the easy way out. But I guess the exam wants to test our understanding of model validation and making sure we don't overfit the data.

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Vallie

5 days ago

Yeah, I agree with Barbra. C seems like the best option here. Although, I do wonder why we can't just use the original dataset for both training and evaluation. Wouldn't that be simpler?

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Barbra

6 days ago

Hmm, I think the answer might be C. We're evaluating the model, so we should use the testing dataset rather than the training dataset. That way we can see how the model performs on data it hasn't seen before.

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Aja

7 days ago

I'm not sure about this question. It seems like it's asking about splitting the dataset, but I'm not clear on the difference between features, labels, training, and testing datasets. I'll have to think through this carefully.

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