from nn import * X = numpy.array([[0, 0], [0, 1], [1, 0], [1, 1]]) T = numpy.array([[1, 0], [0, 1], [0, 1], [1, 0]]) N = X.shape[0] # number of data input_size = X.shape[1] hidden_size = 2 output_size = 2 epsilon = 0.1 mu = 0.9 epoch = 10000 nn = Neural(input_size, hidden_size, output_size) nn.train(X, T, epsilon, mu, epoch) nn.error_graph() C, Y = nn.predict(X) for i in range(N): x = X[i, :] y = Y[i, :] c = C[i] print(x) print(y) print(c) print("")
