def __init__(self,
booster: Booster,
tree_index: int,
x_data,
y_data,
feature_names: List[str] = None,
target_name: str = None,
class_names: (List[str], Mapping[int, str]) = None):
if hasattr(booster, 'get_booster'):
booster = booster.get_booster(
) # support XGBClassifier and XGBRegressor
utils.check_tree_index(tree_index, len(booster.get_dump()))
self.booster = booster
self.tree_index = tree_index
self.tree_to_dataframe = self._get_tree_dataframe()
self.children_left = self._calculate_children(
self.__class__.LEFT_CHILDREN_COLUMN)
self.children_right = self._calculate_children(
self.__class__.RIGHT_CHILDREN_COLUMN)
self.config = json.loads(self.booster.save_config())
self.node_to_samples = None # lazy initialized
self.features = None # lazy initialized
super().__init__(booster, x_data, y_data, feature_names, target_name,
class_names)
def __init__(self,
booster: Booster,
tree_index: int,
x_data: (pd.DataFrame, np.ndarray),
y_data: (pd.Series, np.ndarray),
feature_names: List[str] = None,
target_name: str = None,
class_names: (List[str], Mapping[int, str]) = None):
utils.check_tree_index(tree_index, booster.num_trees())
self.booster = booster
self.tree_index = tree_index
self.tree_nodes, self.children_left, self.children_right = self._get_nodes_info()
self.thresholds = None # lazy evaluation
self.features = None # lazy evaluation
self.node_to_samples = None
super().__init__(booster, x_data, y_data, feature_names, target_name, class_names)