Dinesh Asanka takes us through the cross-validation component in Azure ML Studio:
Let us look at implementing Cross-Validation in Azure Machine Learning. Let us use the sample Adventure Works database that we used for all the articles.
Then Cross Validate Model is dragged and dropped to the experiment. The Cross Validate model has two inputs and two outputs. Two inputs are data input and the relation to the Machine Learning technique. Let us use the Two-Class Decision Jungle as the Machine Learning Technique. Then the first output is connected to the Evaluate Model as shown in the following figure:
Click through for the process.