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Answer: You should make use of the Split Data module.
The question asks for splitting data into two separate datasets in Azure Machine Learning Studio. The Split Data module (Option A) is specifically designed for this purpose, allowing division of datasets into training and testing sets based on specified ratios or criteria. Community discussion strongly supports this with 100% consensus and high upvotes (34 upvotes for the top comment). Comments provide detailed reasoning that Split Data is the correct module for dataset splitting, while other options serve different purposes: Group Categorical Values (B) is for categorical data grouping, Clip Values (C) is for outlier handling, and Group Data into Bins (D) is for binning continuous data, not dataset splitting. Microsoft documentation links provided in comments confirm Split Data as the appropriate module.
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You are building a machine learning experiment in Azure Machine Learning Studio and need to split data into two distinct datasets. Which action should you take?
A
You should make use of the Split Data module.
B
You should make use of the Group Categorical Values module.
C
You should make use of the Clip Values module.
D
You should make use of the Group Data into Bins module.
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