| 20 | |
| 21 | @pytest.fixture |
| 22 | def training_data(): |
| 23 | r = Random(0) |
| 24 | predictors = vectors() |
| 25 | sparse_predictors = sparse_vectors() |
| 26 | response = array() |
| 27 | for i in range(30): |
| 28 | for c in [-1, 1]: |
| 29 | response.append(c) |
| 30 | values = [r.random() + c * 0.5 for _ in range(3)] |
| 31 | predictors.append(vector(values)) |
| 32 | sp = sparse_vector() |
| 33 | for i, v in enumerate(values): |
| 34 | sp.append(pair(i, v)) |
| 35 | sparse_predictors.append(sp) |
| 36 | return predictors, sparse_predictors, response |
| 37 | |
| 38 | |
| 39 | @pytest.mark.parametrize('trainer, class1_accuracy, class2_accuracy', [ |