Step 8. Neural network for XOR

This is a multi-layer neural network to learn XOR from exemplars.



XOR multi-layer ...
Neural network to do XOR.



  • This is a modified port of a neural network to do XOR by the Coding Train.
  • Code from here.
  • Uses two libraries from here.
  • See Coding Train live demo.
  • See video.
  • See long playlist of Coding Train videos: "Neural Networks" explaining the entire program and supporting libraries.

Look at the code

  • See the "tweaker's box" at the top of the code. These are the things you can easily change.

  • Initialise weights strategy:
    • Every time you run it, it starts with random weights.
    • In nn.js see the calls to Matrix.randomize().
    • Matrix.randomize() in matrix.js is edited so that it calls a function randomWeight() that we define in the tweaker's box.
    • Hence we can experiment with different weight initialisations.


Clone and Edit the World.
  1. Change things in the "tweaker's box".

  2. Switch between displaying all squares or just the 4 main squares.

  3. See what happens when you:
    • Change the learning rate to 0.
    • Change the learning rate to 0.01.
    • Change the learning rate to 10.

  4. See what happens when you:
    • Reduce hidden nodes to 1.
    • Increase hidden nodes to 50.

  5. See what happens when you:
    • Change randomWeight to return zero.
    • Change randomWeight to return constant.

  6. Change the exemplars to represent a different function (across 0,1). Tweak it to successfully learn that function from exemplars.
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