(task_type)
| 5058 | |
| 5059 | |
| 5060 | def test_object_importances(task_type): |
| 5061 | train_pool = Pool(TRAIN_FILE, column_description=CD_FILE) |
| 5062 | pool = Pool(TEST_FILE, column_description=CD_FILE) |
| 5063 | |
| 5064 | model = CatBoost({'loss_function': 'RMSE', 'iterations': 10, 'task_type': task_type, 'gpu_ram_part': TEST_GPU_RAM_PART, 'devices': '0'}) |
| 5065 | model.fit(train_pool) |
| 5066 | indices, scores = model.get_object_importance(pool, train_pool, top_size=10) |
| 5067 | oimp_path = test_output_path(OIMP_PATH) |
| 5068 | np.savetxt(oimp_path, scores) |
| 5069 | |
| 5070 | return local_canonical_file(oimp_path) |
| 5071 | |
| 5072 | |
| 5073 | def test_positive_object_importance_per_object(): |
nothing calls this directly
no test coverage detected