How can I evaluate a novelty detection model (e.g.: Local Outlier Factor) that is trained to identify previously unseen data points that do not belong to the training dataset?
My issue is that, unlike in supervised learning (for example), we do not have any test cases that are outside the training dataset, to test against the novelty detection model. Therefore, how can we evaluate if the model can actually identify any novel datapoints?
