| 13 | return X1, y1, X2, y2 |
| 14 | |
| 15 | def gen_non_lin_separable_data(): |
| 16 | mean1 = [-1, 2] |
| 17 | mean2 = [1, -1] |
| 18 | mean3 = [4, -4] |
| 19 | mean4 = [-4, 4] |
| 20 | cov = [[1.0,0.8], [0.8, 1.0]] |
| 21 | X1 = np.random.multivariate_normal(mean1, cov, 50) |
| 22 | X1 = np.vstack((X1, np.random.multivariate_normal(mean3, cov, 50))) |
| 23 | y1 = np.ones(len(X1)) |
| 24 | X2 = np.random.multivariate_normal(mean2, cov, 50) |
| 25 | X2 = np.vstack((X2, np.random.multivariate_normal(mean4, cov, 50))) |
| 26 | y2 = np.ones(len(X2)) * -1 |
| 27 | return X1, y1, X2, y2 |
| 28 | |
| 29 | def gen_lin_separable_overlap_data(): |
| 30 | # generate training data in the 2-d case |