I am working on a multi-class classification problem. I was wondering if there is way to decide if a test sample could not belong to any of the classes in the training set? Simply put I want to classify if the data point belongs to an unseen class - 'others'
For now, I am thinking of extracting probabilities of how much each data point belongs to each class. If these probabilities are skewed (i.e. are weighed highly for some classes and very low for majority of classes), then it belongs to one of the train set classes. If these probabilities are uniform (say almost equally distributed) then it belongs to an others class. But obviously this method might give bad results and I would also need to empirically set the thresholds for uniformity and skewness.