I am having a lot of trouble finding any kind of answers to this problem i am facing.
I have a few text classifiers that i am testing out, and they work well for data that does fit into any predefined category, but if I input, lets just say "fhjakdlfsah", it will still assign it to some category because i guess the predict_proba functionality has to add up to 1 for all of the categories.
Is there something i am missing here? I am having such a hard time finding a solution to this, and I would imagine it is a very common thing to deal with. Right now i am working with gradientboosting from sklearn, and tried wrapping it in a onevsrestclassifier as suggested by others, but it is still having the same thing where all probabilities are adding up to one, and it is getting assigned the highest probability
Basically I am looking for a solution that can say either, yes this fits into one of these categories, or no, this does not fit into any of these categories.
Any help would be greatly appreciated as I am getting quite stuck here