title: When to use a neural network with just one output neuron and when with multiple output neurons?
body: <p>I was trying to understand the difference between the use of a neural network with just one output neuron and one with multiple neurons in the output layers.</p>
  <p><a href="https://i.stack.imgur.com/UrGrT.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/UrGrT.png" alt="enter image description here" /></a></p>
  <p>I know that with this type of neural network I can solve like a XOR logical gate, in fact, I can use a ANN with less neurons in the hidden layers.</p>
  <p><a href="https://i.stack.imgur.com/j2qa7.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/j2qa7.png" alt="enter image description here" /></a>
  <a href="https://i.stack.imgur.com/yzY7D.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/yzY7D.jpg" alt="enter image description here" /></a></p>
  <p>But I am not very clear when and why I should use a neural network with this kind of topology, where is seen that the ANN have multiple neurons in the output layer.</p>
  <p>Does anyone know the difference?</p>