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Question 67 - DP-100 discussion

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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?

A.
Permutation Feature Importance
Answers
A.
Permutation Feature Importance
B.
Filter Based Feature Selection
Answers
B.
Filter Based Feature Selection
C.
Fisher Linear Discriminant Analysis
Answers
C.
Fisher Linear Discriminant Analysis
D.
Synthetic Minority Oversampling Technique (SMOTE)
Answers
D.
Synthetic Minority Oversampling Technique (SMOTE)
Suggested answer: D

Explanation:

Use the SMOTE module in Azure Machine Learning Studio (classic) to increase the number of underrepresented 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.

Reference:

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

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asked 02/10/2024
Roger Warner
33 questions
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