code: def __init__(
      self,
      criterion="squared_error",
      splitter="random",
      max_depth=None,
      min_samples_split=2,
      min_samples_leaf=1,
      max_features=1.0,
      random_state=None,
      max_leaf_nodes=None,
  ):
      super(ExtraTreeQuantileRegressor, self).__init__(
          criterion=criterion,
          splitter=splitter,
          max_depth=max_depth,
          min_samples_split=min_samples_split,
          min_samples_leaf=min_samples_leaf,
          max_features=max_features,
          max_leaf_nodes=max_leaf_nodes,
          random_state=random_state,
      )
  
imports: import logging
  from functools import partial
  import numpy
  import pandas
  from sklearn.ensemble._forest import ForestRegressor
  from sklearn.tree import BaseDecisionTree, DecisionTreeRegressor, ExtraTreeRegressor
  from sklearn.utils import check_array, check_random_state, check_X_y
label_desc: Use image node_id 1 to create a new ExtraTreeQuantileRegressor object from inherited base classes: BaseTreeQuantileRegressor, ExtraTreeRegressor with example: obj = ExtraTreeQuantileRegressor(criterion, splitter, max_depth, min_samples_split, min_samples_leaf, max_features, random_state, max_leaf_nodes)