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You realize that softmax scores aren't probabilities, right? It's just a relative measure of confidence, scaled such that they all sum to 1.0.
by muzakthings 10y ago
You realize that softmax scores aren't probabilities, right?
It's just a relative measure of confidence, scaled such that they all sum to 1.0.
- chipperyman573 10y agoYou can't add any of the numbers in the picture to equal 1.0 (or 100)
- visarga 10y agoWhat you need to do is to take the top prediction and see how accurate it is compared to a test set. The scores on the picture represent confidence not accuracy.
- imh 10y agoThat's kinda true, but (regularization aside) for standard loss functions it's minimized at the point it's well calibrated, right? Given the scores in the image (97% animal, 90% tiger, etc) they seem to be binary classifiers e.g. "is this a tiger?" So of all scores in the neighborhood of 90%, 90% should be "yes it is," making it a measure of confidence compatible with probability. Please someone correct me if I'm wrong, but I'm pretty sure that's how it works, just like how logistic regression gives you a probability.