You are performing feature engineering on a dataset. You must add a feature named CityName and populate the column value with the text London. You need to add the new feature to the dataset. Which Azure Machine Learning Studio module should you use?
The correct answer is D. Apply SQL Transfer
Editing the metadata allows you to rename or change the data type of existing columns. It does not allow you to add a column and set it's value to "London".
To add a new feature with a constant value like "London" for all rows, the most efficient way is to use SQL. The "Apply SQL Transformation" module allows you to execute SQL queries on your dataset, which can easily add a new column with a constant value.
Apply SQL Transformation: This module allows you to use SQL queries to manipulate and transform your dataset. You can easily add a new column and populate it with the desired value using an SQL statement.
This question appears at least twice and is wrong both times. i checked. Edit Metadata cannot add a new column and assign a value. There is, however, a distinct "Add column" component.
Correct answer is D. I have checked this on Azure Designer Studio to make sure. Edit metadata allows you to alter existing columns. However, it doesn't allow you to add a new column or set the value of it. However, you can add a new column and change its value using Apply SQL Transformation.
I think B is correct, Marking columns as features is what the Edit metadata module can do,
Creating new column is not mentioned in the question, It is populate!
The answer should be "Apply SQL Transformation". I have checked it. The metadata does not allow to add new columns
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