def build_tree(self, X, y):
"""
Args:
X: object-features matrix
y: target vector
Returns:
A `BinaryDecisionTree` fitted to the dataset.
The actual structure of the tree depends both on dataset and the parameters
passed to the `TreeBuilderCART` constructor.
"""
n_samples, n_features = X.shape
tree = BinaryDecisionTree(n_features=n_features)
if self.n_jobs > 1:
self.pool = Pool(self.n_jobs)
leaf_to_split = tree.root()
self._build_tree_recursive(tree, leaf_to_split, X, y)
self._prune_tree(tree, X, y)
if TreeBuilderCART.debug:
TreeBuilderCART.logger.debug(tree)
self.pool = None
return tree
