I would like to know whether there is a cut-off probability of outcome when classifying observations into more than 2 classes.
For instance, the threshold in binary logistic regression is usually 0.5, so much so that a probability below 0.5 disfavours the reference outcome.
However, in a three-class problem it seems there are many possibilities. I would assume a cut-off probability of 0.333 here, but what if outcomes A, B and C have a probability of, say, 0.333, 0.666 and 0 respectively? Is there a workaround to get at a cut-off probability in multinomial cases?
The purpose is to use a threshold for the comparison between the model and new data to compute deviations from the model.
By way of illustration, consider the case of a binary choice in which deviation is set to 0 when the actual response (A) conforms to the response predicted by the model (also A). In case of non-conformity, we subtract the threshold of 0.5 from the probability of the predicted outcome to compute the deviation score. Any idea how it could be done in case of 3+ classes?
Thank you very much in advance!