import numpy as np from matplotlib import pyplot as plt from sklearn import datasets from mlpy.model import Layer, NeuralNetwork # Generate dataset n_samples = 400 sigma = 2e-1 X, T = datasets.make_moons(n_samples, noise=sigma) # Fit the neural network max_iter = int(1e2) tol = 1e-5 nn = NeuralNetwork( [Layer('Sigmoid', (2, 3)), Layer('Sigmoid', (3, 4)), Layer('Sigmoid', (4, 5)), Layer('Sigmoid', (5, 1)) ], max_iter=max_iter, tol=tol) nn.check_gradient(X, T)