def main(): w = np.matrix([0., 0.]) index = 0 while True: if (w.dot(paitentData[index].T) > 0) != ( hasCancerData[index] > 0): w += paitentData[index] * hasCancerData[index] index = 0 continue index += 1 if index >= len(hasCancerData): break print w.tolist()[0] #### Do the training here ### mlt.plot_prec(paitentData.tolist(), hasCancerData, w.tolist()[0])
def main(): nn = NeuNet.NeuralNetwork([2, 10, 1]) nn.fit(xor_data, xor_expected) mlt.plot_nn(xor_data, xor_expected, nn)