I am ambiguous about a learning problem.
I am working on a task of anomaly detection. I train a model of only normality patterns, then classify a new sample by its likelihood (or similar quantities). I determine several hyperparameters (e.g. number of training epochs) by cross-validation, in which each evaluation set contains samples of normality and abnormality.
So I want to know your idea about this learning.