def test_predict_all_in_regression(self): model = AutoML(explain_level=0, verbose=0, random_state=1, results_path=self.automl_dir) model.fit(boston.data, boston.target) with self.assertRaises(AutoMLException) as context: # Try to call predict_all in regression task model.predict_all(boston.data)
def test_integration(self): a = AutoML(results_path=self.automl_dir, mode='Compete', algorithms=['Baseline', 'CatBoost', 'LightGBM', 'Xgboost'], stack_models=True, total_time_limit=60, validation_strategy={ "validation_type": "kfold", "k_folds": 3, "shuffle": True, "stratify": True, "random_seed": 123 }) X, y = datasets.make_classification( n_samples=1000, n_features=30, n_informative=29, n_redundant=1, n_classes=8, n_clusters_per_class=3, n_repeated=0, shuffle=False, random_state=0, ) X_train, X_test, y_train, y_test = train_test_split(X, y, train_size=0.8) a.fit(X_train, y_train) p = a.predict_all(X_test) a2 = AutoML(results_path=self.automl_dir) p2 = a2.predict_all(X_test) assert_almost_equal(p["prediction_0"].iloc[0], p2["prediction_0"].iloc[0]) assert_almost_equal(p["prediction_7"].iloc[0], p2["prediction_7"].iloc[0])