Validation options are the same for the following analyses:
This command is available with the Predictive Analytics Module. Click here for more information about how to activate the module.
Choose the validation method to test your model. Usually, with smaller samples, the K-fold cross-validation method is appropriate. With larger samples, you can select a fraction of cases to use for training and testing.
Complete the following steps if you want to use the K-fold cross-validation method to validate the test sample. The K-fold cross-validation method is the default method when the number of rows is ≤ 2000.
Complete the following steps to specify a fraction of the data to use for training and for testing. The Test set validation method is the default method when the number of rows is > 2000. In many cases, 70% of the data is used for training, and 30% of the data is used for testing.