db3d4586a34f3734edf92454b9c16e1511369ddf,skmultiflow/classification/trees/arf_hoeffding_tree.py,RandomLearningNode,learn_from_instance,#RandomLearningNode#Any#Any#Any#Any#,75

Before Change

            self._observed_class_distribution[y] += weight
            if not self.list_attributes:
                self.list_attributes = [None] * self.subspace_size
                for j in range(self.subspace_size):
                    is_unique = False
                    while not is_unique:
                        self.list_attributes[j] = randint(0, self.subspace_size - 1)
                        is_unique = True
                        for i in range(j):
                            if self.list_attributes[j] == self.list_attributes[i]:
                                is_unique = False
                                break

            for j in range(self.subspace_size):
                i = self.list_attributes[j]
                obs = self._attribute_observers[i]
                if obs is None:
                    if i in ht.nominal_attributes:
                        obs = NominalAttributeClassObserver()
                    else:
                        obs = GaussianNumericAttributeClassObserver()
                    self._attribute_observers[i] = obs
                obs.observe_attribute_class(X[i], int(y), weight)

    class LearningNodeNB(RandomLearningNode):
        Naive Bayes learning node class.

After Change

                Hoeffding Tree to update.

            
            try:
                self._observed_class_distribution[y] += weight
            except KeyError:
                self._observed_class_distribution[y] = weight
            if not self.list_attributes:
                population = range(get_dimensions(X)[1])
                self.list_attributes = sample(population, self.subspace_size)

Instances