(preds, labels, output_margin)
| 53 | from sklearn.model_selection import KFold |
| 54 | |
| 55 | def check_pred(preds, labels, output_margin): |
| 56 | if output_margin: |
| 57 | err = sum( |
| 58 | 1 for i in range(len(preds)) if preds[i].argmax() != labels[i] |
| 59 | ) / float(len(preds)) |
| 60 | else: |
| 61 | err = sum(1 for i in range(len(preds)) if preds[i] != labels[i]) / float( |
| 62 | len(preds) |
| 63 | ) |
| 64 | assert err < 0.4 |
| 65 | |
| 66 | X, y = load_iris(return_X_y=True) |
| 67 | kf = KFold(n_splits=2, shuffle=True, random_state=rng) |
no outgoing calls
no test coverage detected