from TrainingPattern import TrainingPattern
from MultiLayerPerceptron import MultiLayerPerceptron
if __name__ == "__main__":
trainingPatterns = [ TrainingPattern([1,0,0,0], [1,0,0,0]),
TrainingPattern([0,1,0,0], [0,1,0,0]),
TrainingPattern([0,0,1,0], [0,0,1,0]),
TrainingPattern([0,0,0,1], [0,0,0,1]) ]
mlp = MultiLayerPerceptron(inputLayerSize=4, hiddenLayersSize=[2], outputLayerSize=4, epochs=10000, learningStep=0.5, biasNeuron=True)
mlp.train(trainingPatterns)
for tp in trainingPatterns:
out = mlp.calculateNetworkOutput(tp)
print("Actual output : {} mlp returned : {}".format(tp.outputs, out))
