code: def __init__(
      self,
      split_criterion="gini",
      max_tree_depth=1,
      min_observations_in_leaf_node=1,
      max_iterations=100,
      learning_rate=1.0,
      accuracy_threshold=0.01,
  ):
      self.split_criterion = split_criterion
      self.max_tree_depth = max_tree_depth
      self.min_observations_in_leaf_node = min_observations_in_leaf_node
      self.max_iterations = max_iterations
      self.learning_rate = learning_rate
      self.accuracy_threshold = accuracy_threshold
  
file_path: scikit-learn-intelex/daal4py/sklearn/ensemble/AdaBoostClassifier.py
imports: import numbers
  import numpy
  from sklearn import __version__
  from sklearn import preprocessing
  from sklearn.base import BaseEstimator, ClassifierMixin
  from sklearn.utils.multiclass import check_classification_targets
  from sklearn.utils.validation import check_array, check_is_fitted, check_X_y
  import daal4py
  from .._utils import control_n_jobs, getFPType, run_with_n_jobs
label_desc: Use image node_id 1 to create a new AdaBoostClassifier object from inherited base classes: BaseEstimator, ClassifierMixin with example: obj = AdaBoostClassifier(split_criterion, max_tree_depth, min_observations_in_leaf_node, max_iterations, learning_rate, accuracy_threshold)