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Answer: Execute Python Script
The question requires adding a new column named 'CityName' with the value 'London' for every row. The Execute Python Script module (Option C) is the correct choice because it allows custom Python code to manipulate the dataset, including adding new columns and populating them with specific values. The Edit Metadata module (Option A) only modifies existing column metadata (e.g., data types, roles) but cannot create new columns or set their values. Filter Based Feature Selection (Option B) is for selecting existing features based on statistical criteria, not adding new ones. Latent Dirichlet Allocation (Option D) is for topic modeling and unrelated to column addition. The community discussion strongly supports Option C, with the highest upvoted comments (e.g., 58 upvotes for RSMCT2011) and detailed reasoning confirming that Edit Metadata lacks the capability to add columns or populate values, while Execute Python Script provides the necessary flexibility.
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You are performing feature engineering on a dataset. You need to add a new feature named CityName where every row has the value London. Which module should you use in Azure Machine Learning Studio?
A
Edit Metadata
B
Filter Based Feature Selection
C
Execute Python Script
D
Latent Dirichlet Allocation