Softmax and cross-entropy · MAAI7602 Applied Computer Vision

A classifier outputs one score per class, called logits. Softmax turns them into probabilities; cross-entropy is minus the log of the probability given to the correct class. How are class scores converted into probabilities, and how does cross-entropy measure the error of a prediction?

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