I'm trying to build a text classification model with SVM. The training data set consists of 100 string records with a one-to-one mapped response variable which is also a string. I can't split the data into training and test sets because there are 100 different classes in the response variable.
When I try to predict a new input, the model returns a response, but my question is is there any way to quantify this? Why I want to do this is if the model sees a totally new input, then based on some threshold on this metric, I can write some code to give feedback like "Can't predict as it is not trained before."