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You are building a classification experiment in Azure Machine Learning. You need to ensure that you can use the Evaluate Model module in the experiment. Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Correct Answer: B,C
Explanation/Reference: Explanation: Use the training data. To evaluate a model, you must connect a dataset that contains a set of input columns and scores. If no other data is available, you can use your original dataset. 1. Connect the Scored dataset output of the Score Model to the input of Evaluate Model. 2. Click Evaluate Model module, and select Run selected to generate the evaluation scores. Use testing data A common scenario in machine learning is to separate your original data set into training and testing datasets, using the Split module, or the Partition and Sample module. 1. Connect the Scored dataset output of the Score Model to the input of Evaluate Model. 2. Connect the output of the Split Data module that contains the testing data to the right-hand input of Evaluate Model. 3. Click Evaluate Model module, and select Run selected to generate the evaluation scores. References: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/evaluate- model
