The SoftMax Function is a generalization of the logistic function to multiple dimensions. It is also known as softargmax or normalized exponential function. It is used in multinomial logistic regression and is often used as the last activation function of a neural network to normalize the output of a network. Thus, it is used to a probability distribution over predicted output vectors. SoftMax function cannot be used as an activation function, but it can be used as a final step after having all outputs from the activation function, then we can normalize this vector (or array) by the SoftMax.

https://learncplusplus.org/what-is-the-softmax-function-in-neural-networks/

https://learncplusplus.org/what-is-the-softmax-function-in-neural-networks/

The SoftMax Function is a generalization of the logistic function to multiple dimensions. It is also known as softargmax or normalized exponential function. It is used in multinomial logistic regression and is often used as the last activation function of a neural network to normalize the output of a network. Thus, it is used to a probability distribution over predicted output vectors. SoftMax function cannot be used as an activation function, but it can be used as a final step after having all outputs from the activation function, then we can normalize this vector (or array) by the SoftMax.
https://learncplusplus.org/what-is-the-softmax-function-in-neural-networks/

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