Softmax function

The softmax function, also known as softargmax^: 184 or normalized exponential function,^: 198 converts a vector of $K$ real numbers into a probability distribution of $K$ possible outcomes. It is a generalization of the logistic function to multiple dimensions, and used in multinomial logistic regression. The softmax function is often used as the last activation function of a neural network to normalize the output of a network to a probability distribution over predicted output classes, based on Luce's choice axiom.

Machine learning and data mining
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