DRAG DROP -
You are analyzing a raw dataset that requires cleaning.
You must perform transformations and manipulations by using Azure Machine Learning Studio.
You need to identify the correct modules to perform the transformations.
Which modules should you choose? To answer, drag the appropriate modules to the correct scenarios. Each module may be used once, more than once, or not at all.
You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Select and Place:
 
















 

Suggested Answer: 
    

Box 1: Clean Missing Data -
Box 2: SMOTE -
Use the SMOTE module in Azure Machine Learning Studio 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.
Box 3: Convert to Indicator Values
Use the Convert to Indicator Values module in Azure Machine Learning Studio. The purpose of this module is to convert columns that contain categorical values into a series of binary indicator columns that can more easily be used as features in a machine learning model.
Box 4: Remove Duplicate Rows -
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote
 https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/convert-to-indicator-values

This question is in DP-100 Exam
For getting Microsoft Azure Data Scientist Associate Certificate


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