def test_fit_optimize_auc(self):
automl = AutoML(
total_time_limit=5,
algorithms=["Xgboost"],
start_random_models=2,
hill_climbing_steps=0,
optimize_metric="auc",
seed=16,
)
automl.fit(self.X, self.y)
ldb = automl.get_leaderboard()
self.assertEqual(ldb["metric_type"][0], "auc")
self.assertEqual(np.sum(ldb["metric_value"] > 0.5),
ldb.shape[0]) # all better than 0.5 AUC
def test_predict_labels(self):
automl = AutoML(
total_time_limit=15,
algorithms=["Xgboost"],
start_random_models=5,
hill_climbing_steps=0,
train_ensemble=True,
seed=15,
)
automl.fit(self.X, self.y)
ldb = automl.get_leaderboard()
self.assertEqual(ldb.shape[0], len(automl._models))
for col in [
"uid", "model_type", "metric_type", "metric_value",
"train_time"
]:
self.assertTrue(col in ldb.columns)