title: How best to deal with "None of the above" in Image Classification?
body: <p>This seems to be a fundamental question which some of you out there must have an opinion on.  I have an image classifier implemented in CNTK with 48 classes.  If the image does not match any of the 48 classes very well, then I'd like to be able to conclude that it was not among these 48 image types.  My original idea was simply that if the highest output of the final Softmax layer was low, I would be able to conclude that the test image matched none well.  While I occasionally see this occur, in most testing, Softmax still produces a very high (and mistaken) result when handed an 'unknown image type'.  But maybe my network is 'over fit' and if it wasn't, my original idea would work fine.  What do you think?  Any way to define a 49-th class called 'none-of-the-above'?</p>