Softmax Activation Function

A vector of numbers is transformed into a vector of probabilities via the mathematical operation known as Softmax, where the probability of each value are inversely proportional to the relative scale of each value in the vector.

The softmax activation function is most frequently used as an activation function in neural network models in applied machine learning. The network is specifically set up to produce N values, one for each class in the classification task. The outputs are then normalised using the softmax function, changing them from weighted sum values to probabilities that total to 1. Each value in the softmax function's output is regarded as the likelihood that a given class will contain that value.A probabilistic or "softer" variation of the argmax function is the softmax, sometimes known as "soft max," mathematical function.

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