def test_invalid_verbose(self):
model = AutoML(explain_level=0,
verbose=0,
results_path=self.automl_dir)
param = {"verbose": -1}
model.set_params(**param)
with self.assertRaises(ValueError) as context:
model.fit(iris.data, iris.target)
def test_invalid_algorithm_name(self):
model = AutoML(explain_level=0,
verbose=0,
results_path=self.automl_dir)
param = {"algorithms": ["Baseline", "Neural Netrk"]}
model.set_params(**param)
with self.assertRaises(ValueError) as context:
model.fit(iris.data, iris.target)
def test_invalid_validation_strategy(self):
model = AutoML(explain_level=0, verbose=0)
param = {"validation_strategy": "test"}
model.set_params(**param)
with self.assertRaises(ValueError) as context:
model.fit(iris.data, iris.target)
def test_invalid_eval_metric(self):
model = AutoML(explain_level=0, verbose=0)
param = {"eval_metric": "not_real_metric"}
model.set_params(**param)
with self.assertRaises(ValueError) as context:
model.fit(iris.data, iris.target)
def test_invalid_stack_models(self):
model = AutoML(explain_level=0, verbose=0)
param = {"stack_models": "not bool"}
model.set_params(**param)
with self.assertRaises(ValueError) as context:
model.fit(iris.data, iris.target)
def test_invalid_model_time_limit(self):
model = AutoML(explain_level=0, verbose=0)
param = {"algorithms": ["Baseline", "Neural Netrk"]}
model.set_params(**param)
with self.assertRaises(ValueError) as context:
model.fit(iris.data, iris.target)
def test_invalid_model_time_limit(self):
model = AutoML(explain_level=0, verbose=0)
param = {"model_time_limit": -1}
model.set_params(**param)
with self.assertRaises(ValueError) as context:
model.fit(iris.data, iris.target)
def test_invalid_tuning_mode(self):
model = AutoML(explain_level=0, verbose=0)
param = {"results_path": 2}
model.set_params(**param)
with self.assertRaises(ValueError) as context:
model.fit(iris.data, iris.target)
