def test_early_stopping(caplog, linear_regression_pipeline_class,
X_y_regression):
X, y = X_y_regression
tolerance = 0.005
patience = 2
automl = AutoMLSearch(X_train=X,
y_train=y,
problem_type='regression',
objective='mse',
max_time='60 seconds',
patience=patience,
tolerance=tolerance,
allowed_model_families=['linear_model'],
random_state=0,
n_jobs=1)
mock_results = {'search_order': [0, 1, 2], 'pipeline_results': {}}
scores = [150, 200, 195]
for id in mock_results['search_order']:
mock_results['pipeline_results'][id] = {}
mock_results['pipeline_results'][id]['score'] = scores[id]
mock_results['pipeline_results'][id][
'pipeline_class'] = linear_regression_pipeline_class
automl._results = mock_results
automl._check_stopping_condition(time.time())
out = caplog.text
assert "2 iterations without improvement. Stopping search early." in out
def test_early_stopping(caplog, logistic_regression_binary_pipeline_class, X_y_binary):
X, y = X_y_binary
with pytest.raises(ValueError, match='patience value must be a positive integer.'):
automl = AutoMLSearch(X_train=X, y_train=y, problem_type='binary', objective='AUC', max_iterations=5, allowed_model_families=['linear_model'], patience=-1, random_seed=0)
with pytest.raises(ValueError, match='tolerance value must be'):
automl = AutoMLSearch(X_train=X, y_train=y, problem_type='binary', objective='AUC', max_iterations=5, allowed_model_families=['linear_model'], patience=1, tolerance=1.5, random_seed=0)
automl = AutoMLSearch(X_train=X, y_train=y, problem_type='binary', objective='AUC', max_iterations=5,
allowed_model_families=['linear_model'], patience=2, tolerance=0.05,
random_seed=0, n_jobs=1)
mock_results = {
'search_order': [0, 1, 2],
'pipeline_results': {}
}
scores = [0.95, 0.84, 0.96] # 0.96 is only 1% greater so it doesn't trigger patience due to tolerance
for id in mock_results['search_order']:
mock_results['pipeline_results'][id] = {}
mock_results['pipeline_results'][id]['score'] = scores[id]
mock_results['pipeline_results'][id]['pipeline_class'] = logistic_regression_binary_pipeline_class
automl._results = mock_results
automl._check_stopping_condition(time.time())
out = caplog.text
assert "2 iterations without improvement. Stopping search early." in out
