Hey I'm stuck with this Machine Learning exercise, I need some serious help!

Solve the following three-bit parity problem, with a 3-3-1 network with bias. That is, the input layer has three nodes, the hidden layer has three nodes and the output layer has one node. a) Analyze the function of the hidden layer, just like what we did about the XOR problem in class. b) Retrain several times from a new random point until you get a local (but not global) minimum. Analyze the function of the hidden units now. c) How many examples are properly classied for your local minimum?

Input Output

0 0 0 0

0 0 1 1

0 1 0 1

0 1 1 0

1 0 0 1

1 0 1 0

1 1 0 0

1 1 1 1