You need to visually identify whether outliers exist in the Age column and quantify the outliers before the outliers are removed.
Which three Azure Machine Learning Studio modules should you use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Create Scatterplot

B. Summarize Data

C. Clip Values

D. Replace Discrete Values

E. Build Counting Transform






 

Suggested Answer: ABC

B: To have a global view, the summarize data module can be used. Add the module and connect it to the data set that needs to be visualized.
A: One way to quickly identify Outliers visually is to create scatter plots.
C: The easiest way to treat the outliers in Azure ML is to use the Clip Values module. It can identify and optionally replace data values that are above or below a specified threshold.
You can use the Clip Values module in Azure Machine Learning Studio, to identify and optionally replace data values that are above or below a specified threshold. This is useful when you want to remove outliers or replace them with a mean, a constant, or other substitute value.
Reference:
https://blogs.msdn.microsoft.com/azuredev/2017/05/27/data-cleansing-tools-in-azure-machine-learning/
 https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clip-values

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


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