Creating an Artifical Neural Network that produces a set of possible outputs
You don't need to scale the output data. For classification with a ANN the best activation is the softmax function:

f(x) = e^x_i / sum e^x_j


Which normalizes an input vector by applying the exponential function element wise, then dividing by the sum. This produces a discrete probability distribution.

Then your output layer should have 5 output neurons, apply softmax, and you will get a discrete probability distribution over the set [0, 1, 2, 3, 4]. Then you don't need to normalize the data, just do a one-hot encoding. Note that this might differ depending on the framework used.