Note: If you choose Custom, you must enter the assumed prior probabilities for each of the classes in the Custom Prior Probabilities text field.
Note: When you choose this option, the performance metrics (Root Mean Square Error, MAE, and Accuracy) are adjusted to assign equal prevalences to the classes. Choose Proportional when the prior probabilities of the groups are equal to those of the input data set. Choose Custom when you want to specify your own prior probabilities / prevalences. This is useful in cases where you have prior knowledge about what they are and want them to influence the posterior probabilities.