def test_grid_search(self):
# Test that the best estimator contains the right value for foo_param
clf = MockClassifier()
grid_search = ATGridSearchCV(clf, {'foo_param': [1, 2, 3]},
verbose=3,
webserver_url=self.live_server_url)
# make sure it selects the smallest parameter in case of ties
old_stdout = sys.stdout
sys.stdout = StringIO()
wait(grid_search.fit(X, y))
sys.stdout = old_stdout
self.assertIn(grid_search.best_estimator_.foo_param, [2, 3])
_mock_sort = partial(_sort_grid_scores, param='foo_param')
for idx, tup in enumerate(
sorted(grid_search.grid_scores_, key=cmp_to_key(_mock_sort))):
self.assertEqual(tup[0], {'foo_param': idx + 1},
'%d%s' % (idx, tup))
# Smoke test the score etc:
grid_search.score(X, y)
grid_search.predict_proba(X)
grid_search.decision_function(X)
grid_search.transform(X)
# Test exception handling on scoring
grid_search.scoring = 'sklearn'
self.assertRaises(ValueError, grid_search.fit, X, y)
def test_grid_search_no_score(self):
# Test grid-search on classifier that has no score function.
clf = LinearSVC(random_state=0)
X, y = make_blobs(random_state=0, centers=2)
Cs = [.1, 1, 10]
clf_no_score = LinearSVCNoScore(random_state=0)
grid_search = ATGridSearchCV(clf, {'C': Cs},
scoring='accuracy',
webserver_url=self.live_server_url)
wait(grid_search.fit(X, y))
grid_search_no_score = ATGridSearchCV(
clf_no_score, {'C': Cs},
scoring='accuracy',
webserver_url=self.live_server_url)
# smoketest grid search
wait(grid_search_no_score.fit(X, y))
# check that best params are equal
try:
assert_equal(grid_search_no_score.best_params_,
grid_search.best_params_)
except AssertionError:
if grid_search.best_params_ == {'C': 1}:
assert_equal(grid_search_no_score.best_params_, {'C': 10})
else:
assert_equal(grid_search_no_score.best_params_, {'C': 1})
# check that we can call score and that it gives the correct result
assert_equal(grid_search.score(X, y), grid_search_no_score.score(X, y))
# giving no scoring function raises an error
grid_search_no_score = ATGridSearchCV(
clf_no_score, {'C': Cs}, webserver_url=self.live_server_url)
assert_raise_message(TypeError,
"no scoring",
grid_search_no_score.fit, [[1]],
webserver_url=self.live_server_url)