MACHINE LEARNING

Detailed explanation-1: -The softmax function is used as the activation function in the output layer of neural network models that predict a multinomial probability distribution. That is, softmax is used as the activation function for multi-class classification problems where class membership is required on more than two class labels.

Detailed explanation-2: -Softmax extends this idea into a multi-class world. That is, Softmax assigns decimal probabilities to each class in a multi-class problem. Those decimal probabilities must add up to 1.0. This additional constraint helps training converge more quickly than it otherwise would.

Detailed explanation-3: -Softmax: Multiclass Neural Networks. Softmax activation function or normalized exponential function is a generalization of the logistic function that turns a vector of K real values into a vector of K real values that sum to 1.