def test_default_configuration_iterative_fit(self):
for i in range(10):
predictions, targets = \
_test_classifier_iterative_fit(MultinomialNB)
self.assertAlmostEqual(
0.97999999999999998,
sklearn.metrics.accuracy_score(predictions, targets))
def test_default_configuration_iterative_fit(self):
for i in range(10):
predictions, targets = \
_test_classifier_iterative_fit(GradientBoostingClassifier)
self.assertAlmostEqual(
0.95999999999999996,
sklearn.metrics.accuracy_score(predictions, targets))
def test_default_configuration_iterative_fit(self):
for i in range(10):
predictions, targets = \
_test_classifier_iterative_fit(BernoulliNB)
self.assertAlmostEqual(0.26000000000000001,
sklearn.metrics.accuracy_score(predictions,
targets))
def test_default_configuration_iterative_fit(self):
for i in range(10):
predictions, targets = \
_test_classifier_iterative_fit(RandomForest)
self.assertAlmostEqual(0.95999999999999996,
sklearn.metrics.accuracy_score(
predictions, targets))
def test_default_configuration_iterative_fit(self):
for i in range(10):
predictions, targets = _test_classifier_iterative_fit(
SGD)
self.assertAlmostEqual(1.0,
sklearn.metrics.accuracy_score(
predictions, targets))
def test_default_configuration_digits_iterative_fit(self):
for i in range(10):
predictions, targets = _test_classifier_iterative_fit(
SGD, dataset='digits')
self.assertAlmostEqual(
0.89313904068002425,
sklearn.metrics.accuracy_score(predictions, targets))
def test_default_configuration_iterative_fit(self):
for i in range(10):
predictions, targets = \
_test_classifier_iterative_fit(MultinomialNB)
self.assertAlmostEqual(0.97999999999999998,
sklearn.metrics.accuracy_score(predictions,
targets))
def test_default_configuration_iterative_fit(self):
for i in range(10):
predictions, targets = \
_test_classifier_iterative_fit(BernoulliNB)
self.assertAlmostEqual(
0.26000000000000001,
sklearn.metrics.accuracy_score(predictions, targets))
def test_default_configuration_digits_iterative_fit(self):
for i in range(10):
predictions, targets = _test_classifier_iterative_fit(classifier=PassiveAggressive,
dataset='digits')
self.assertAlmostEqual(0.91924711596842745,
sklearn.metrics.accuracy_score(
predictions, targets))
def test_default_configuration_digits_iterative_fit(self):
for i in range(10):
predictions, targets = _test_classifier_iterative_fit(
SGD,
dataset='digits')
self.assertAlmostEqual(0.89313904068002425,
sklearn.metrics.accuracy_score(
predictions, targets))
def test_default_configuration_iterative_fit(self):
for i in range(10):
predictions, targets = _test_classifier_iterative_fit(SGD)
self.assertAlmostEqual(
1.0, sklearn.metrics.accuracy_score(predictions, targets))
