def main():
learning_rate = 0.6
beta = 0.7
inner_size = 128
topology = [INPUT_SIZE, inner_size, OUTPUT_SIZE]
activation = lambda x: sigmoid(x, beta)
activation_diff = lambda x: sigmoid_diff(x, beta)
network = NeuralNetwork(topology, activation, activation_diff)
for i in xrange(200):
network.training_session(DATA, 100, learning_rate)
network.test_effectiveness(DATA, 200)
