Interesting. Is this the setting for SAS? Because I usually just split the data into training and testing, and evaluate model performance on test data. As far as I am concerned, validation data is in cross validation where we need to select optimal hyper parameters, so we further split our training data set into training and validation. But we still evaluate model performance based on test data. It is exactly because observations in the test data are not entered into the training process, test data can be used to evaluate the model performance. Because in the end, we determine whether a prediction is a good one based on new data, not on the old or historical data. So I am indeed confused about the SAS norm to set training, validation and test data....
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