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])
