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))