def test_base():
"""Check BaseEnsemble methods."""
tree = DecisionTreeClassifier()
ensemble = BaseEnsemble(base_estimator=tree, n_estimators=3)
ensemble._make_estimator()
ensemble._make_estimator()
ensemble._make_estimator()
assert_equal(3, len(ensemble))
assert_equal(3, len(ensemble.estimators_))
def test_base():
"""Check BaseEnsemble methods."""
tree = DecisionTreeClassifier()
ensemble = BaseEnsemble(base_estimator=tree, n_estimators=3)
ensemble._make_estimator()
ensemble._make_estimator()
ensemble._make_estimator()
ensemble._make_estimator(append=False)
assert_equal(3, len(ensemble))
assert_equal(3, len(ensemble.estimators_))
assert_true(isinstance(ensemble[0], DecisionTreeClassifier))
def __init__(self,
n_classifier=10,
base_estimator="HoeffdingTree",
buffer_size=1000):
self.current_instance_number = 0
self.n_classifier = n_classifier
self.buffer_size = buffer_size
self.instances_bag_X = []
self.instances_bag_Y = []
# self.L = -1 #number of labels (for multi-label compatibility)
for i in range(0, self.n_classifier):
self.instances_bag_X.append([])
self.instances_bag_Y.append([])
self.baseEns = BaseEnsemble.__init__(self,
base_estimator=base_estimator)
def test_base():
"""Check BaseEnsemble methods."""
tree = DecisionTreeClassifier()
ensemble = BaseEnsemble(base_estimator=tree, n_estimators=3)
ensemble._make_estimator()
ensemble._make_estimator()
ensemble._make_estimator()
ensemble._make_estimator(append=False)
assert_equal(3, len(ensemble))
assert_equal(3, len(ensemble.estimators_))
assert_true(isinstance(ensemble[0], DecisionTreeClassifier))
def test_base():
"""Check BaseEnsemble methods."""
tree = DecisionTreeClassifier()
ensemble = BaseEnsemble(base_estimator=tree, n_estimators=3)
ensemble._make_estimator()
ensemble._make_estimator()
ensemble._make_estimator()
assert_equal(3, len(ensemble))
assert_equal(3, len(ensemble.estimators_))
