I have read few articles some say there is no need to have no. of units in output layer = no. of classes why some say they both should be equal.
My questions are
If no. of neurons = no. of classes. How are the classes mapped to each neuron/unit in the output layer. To elaborate how does Neural Network decide which neuron/unit deals with which class.
After training a neural network using tensorflow on a multiclass classification problem using softmax in out put layer and no. of units in output layer = no. of classes. When I use this trained network on test sample, the output is a numpy array of probabilities of each class. How do I whther the first element of that array represents which class.
If no. of units is not equal to no. of classes can some one share a link of such an example for multiclass problems.