def create_immediate_children(self):
assert self.mydataframe is not None, "create_child_nodes called with no dataframe"
assert self.target_attribute is not None, "create child nodes called with no target_attribute"
# TODO keeping track of columns still available to be split on subsequent nodes would allow us to feed the column list into
# TODO determine best split. This would cut back on checks therein (depending on how expensive pandas.unique is)
split_column, split_values, score = MathFunctions.determine_best_split(
self.mydataframe, self.target_attribute)
# if no available split, then this is a leaf.
if not split_column:
target_classes = self.mydataframe[self.target_attribute].unique()
assert len(target_classes) == 1
self.leaf_class = target_classes[0]
# otherwise, make more nodes
else:
self.score = score
self.decision_attribute = split_column
for single_split in split_values:
new_child = Node(parent_node=self)
new_child.depth = self.depth + 1
new_child.target_attribute = self.target_attribute
child_dataframe = self.mydataframe.loc[
self.mydataframe[split_column].isin(single_split)]
new_child.mydataframe = child_dataframe
new_child_edge = self.child_edge()
new_child_edge.node_ptr = new_child
new_child_edge.split_portion = single_split
self.child_edges.append(new_child_edge)
def test_determine_split(self):
assert self.target_attribute in self.mydataframe.columns, self.target_attribute + " was not in column map"
split_column, split_values, trash = MathFunctions.determine_best_split(
self.mydataframe, self.target_attribute)
return (split_column, split_values)
