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Microsoft DP-100 Exam - Topic 1 Question 1 Discussion

Actual exam question for Microsoft's DP-100 exam
Question #: 1
Topic #: 1
[All DP-100 Questions]

You are solving a classification task.

The dataset is imbalanced.

You need to select an Azure Machine Learning Studio module to improve the classification accuracy.

Which module should you use?

Show Suggested Answer Hide Answer
Suggested Answer: C

Use the SMOTE module in Azure Machine Learning Studio (classic) to increase the number of underepresented cases in a dataset used for machine learning. SMOTE is a better way of increasing the number of rare cases than simply duplicating existing cases.

You connect the SMOTE module to a dataset that is imbalanced. There are many reasons why a dataset might be imbalanced: the category you are targeting might be very rare in the population, or the data might simply be difficult to collect. Typically, you use SMOTE when the class you want to analyze is under-represented.


https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote

by Loren at May 03, 2022, 06:40 PM

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Aliza
4 months ago
Not sure if SMOTE is the best choice here...
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Joanna
4 months ago
Wait, does SMOTE really help that much?
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Lawrence
4 months ago
Definitely going with SMOTE for better accuracy!
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Alline
4 months ago
I think Fisher Linear Discriminant Analysis could work too.
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Denise
5 months ago
SMOTE is great for imbalanced datasets!
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Macy
5 months ago
I could be wrong, but I thought Filter Based Feature Selection was more about selecting features rather than dealing with class imbalance.
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Otis
5 months ago
I practiced a similar question, and I think the answer was SMOTE because it helps to generate synthetic samples for the minority class.
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Estrella
5 months ago
I'm not entirely sure, but I feel like Fisher Linear Discriminant Analysis is more about dimensionality reduction than directly addressing imbalance.
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Joesph
5 months ago
I remember studying about handling imbalanced datasets, and I think SMOTE was mentioned as a good technique for that.
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Diego
5 months ago
Hmm, I'm not totally sure about the color options here. I'll have to think it through carefully.
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Miriam
5 months ago
I'm a little confused by option D. Scaling the predictions to get a higher AUC doesn't seem like a legitimate way to improve the model. I think I'll focus my efforts on hyperparameter tuning and see if I can get that AUC up.
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Heidy
5 months ago
Hmm, I'm not totally sure about this one. The question is a bit vague, and the options don't seem to match up perfectly. I might need to re-read it a few times to make sure I understand what they're asking.
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Wenona
5 months ago
I remember discussing the importance of standardizing data models, but I'm not sure if that applies here.
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Lura
5 months ago
This seems like a straightforward question about union strikes. I'm pretty confident I can identify the correct answer.
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