Answer-first summary for fast verification
Answer: No
The correct answer is B (No) because the 'Replace with median' option in Azure ML Studio's Clean Missing Data module only applies to columns with Integer or Double data types, as confirmed by Microsoft documentation. The question does not specify the data types in the dataset, which could include categorical/text columns where median replacement is inappropriate. While median is robust for numerical data with outliers, it cannot handle categorical data, making it an incomplete solution for an unspecified dataset. The community discussion shows mixed opinions, but the most technically accurate comments (with supporting documentation) and the consideration of data type limitations support answer B.
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You are creating a machine learning model and have a dataset containing null and missing values. You plan to use the Clean Missing Data module in Azure Machine Learning Studio to handle these values.
Recommendation: Use the "Replace with median" option.
Does this recommendation satisfy the requirement to detect and fix the null and missing values?
A
Yes
B
No