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)