code: def __init__(
      self,
      loss,
      learning_rate,
      min_samples_leaf,
      max_depth,
      max_leaf_nodes,
      max_bins,
      l2_regularization,
      early_stop,
      tol,
      scoring,
      n_iter_no_change=0,
      validation_fraction=None,
      random_state=None,
      verbose=0,
  ):
      self.loss = loss
      self.learning_rate = learning_rate
      self.max_iter = self.get_max_iter()
      self.min_samples_leaf = min_samples_leaf
      self.max_depth = max_depth
      self.max_leaf_nodes = max_leaf_nodes
      self.max_bins = max_bins
      self.l2_regularization = l2_regularization
      self.early_stop = early_stop
      self.tol = tol
      self.scoring = scoring
      self.n_iter_no_change = n_iter_no_change
      self.validation_fraction = validation_fraction
      self.random_state = random_state
      self.verbose = verbose
      self.estimator = None
      self.fully_fit_ = False
  
file_path: auto-sklearn/autosklearn/pipeline/components/regression/gradient_boosting.py
imports: from typing import Optional
  import numpy
  from ConfigSpace.conditions import EqualsCondition, InCondition
  from ConfigSpace.configuration_space import ConfigurationSpace
  from ConfigSpace.hyperparameters import CategoricalHyperparameter, Constant, UniformFloatHyperparameter, UniformIntegerHyperparameter, UnParametrizedHyperparameter
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  from autosklearn.pipeline.components.base import AutoSklearnRegressionAlgorithm, IterativeComponent
  from autosklearn.pipeline.constants import DENSE, PREDICTIONS, UNSIGNED_DATA
  from autosklearn.util.common import check_none
label_desc: Use image node_id 1 to create a new GradientBoosting object from inherited base classes: IterativeComponent, AutoSklearnRegressionAlgorithm with example: obj = GradientBoosting(loss, learning_rate, min_samples_leaf, max_depth, max_leaf_nodes, max_bins, l2_regularization, early_stop, tol, scoring, n_iter_no_change, validation_fraction, random_state, verbose)