def test_default_configuration_iterative_fit(self):
for i in range(10):
predictions, targets = \
_test_regressor_iterative_fit(ExtraTreesRegressor)
self.assertAlmostEqual(
0.4269923975466271,
sklearn.metrics.r2_score(targets, predictions))
def test_default_configuration_digits_iterative_fit(self):
for i in range(10):
predictions, targets = _test_regressor_iterative_fit(
SGD, dataset='boston')
self.assertAlmostEqual(
-2.9165866511775519e+31,
sklearn.metrics.r2_score(y_true=targets, y_pred=predictions))
def test_default_configuration_iterative_fit(self):
for i in range(10):
predictions, targets = \
_test_regressor_iterative_fit(RandomForest)
self.assertAlmostEqual(
0.41224692924630502,
sklearn.metrics.r2_score(y_true=targets, y_pred=predictions))
def test_default_configuration_digits_iterative_fit(self):
for i in range(10):
predictions, targets = _test_regressor_iterative_fit(SGD,
dataset='boston')
self.assertAlmostEqual(-2.9165866511775519e+31,
sklearn.metrics.r2_score(y_true=targets,
y_pred=predictions))
def test_default_configuration_iterative_fit(self):
for i in range(10):
predictions, targets = \
_test_regressor_iterative_fit(ExtraTreesRegressor)
self.assertAlmostEqual(0.4269923975466271,
sklearn.metrics.r2_score(targets,
predictions))
def test_default_configuration_iterative_fit(self):
for i in range(10):
predictions, targets = \
_test_regressor_iterative_fit(RandomForest)
self.assertAlmostEqual(0.41224692924630502,
sklearn.metrics.r2_score(y_true=targets, y_pred=predictions))
def test_default_configuration_iterative_fit(self):
for i in range(10):
predictions, targets = _test_regressor_iterative_fit(SGD)
self.assertAlmostEqual(
0.092460881802630235,
sklearn.metrics.r2_score(y_true=targets, y_pred=predictions))
def test_default_configuration_iterative_fit(self):
for i in range(10):
predictions, targets = _test_regressor_iterative_fit(SGD)
self.assertAlmostEqual(0.092460881802630235,
sklearn.metrics.r2_score(y_true=targets,
y_pred=predictions))
