# What should the range of the output layer be when performing classification?

I am working on a MLP neural networks, using supervised learning (2 classes and multi-class classification problems). For the hidden layers, I am using $$\tanh$$ (which produces an output in the range $$[-1, 1]$$) and for the output layer a softmax (which gives the probability distribution between $$0$$ and $$1$$). As I am working with supervised learning, should be my targets output between 0 and 1, or $$-1$$ and $$1$$ (because of the $$\tanh$$ function), or it does not matter?

The loss function is quadratic (MSE).

• Quadratic mse for softmax is not recommended. Try cross entropy loss. – DuttaA Mar 8 '19 at 13:59