code: def fit(self, X, y, sample_weight=None, queue=None):
      return self._fit(
          X,
          y,
          sample_weight,
          _backend.decision_forest.classification,
          queue,
      )
  
imports: import numbers
  import warnings
  from abc import ABCMeta, abstractmethod
  from math import ceil
  from numbers import Number
  import numpy
  from scipy import sparse
  from sklearn.ensemble import BaseEnsemble
  from sklearn.exceptions import DataConversionWarning
  from sklearn.utils import check_array, check_random_state, compute_sample_weight, deprecated
  from sklearn.utils.validation import _num_samples, check_consistent_length, check_is_fitted
  from daal4py.sklearn._utils import daal_check_version, sklearn_check_version
  from onedal import _backend
  from ..common._estimator_checks import _check_is_fitted
  from ..common._mixin import ClassifierMixin, RegressorMixin
  from ..common._policy import _get_policy
  from ..datatypes import _convert_to_supported, from_table, to_table
  from ..utils import _check_array, _check_n_features, _check_X_y, _column_or_1d, _validate_targets
label_desc: Use image node_id 3 for calling the ExtraTreesClassifier obj's underlying member method code with example usage: obj.fit(X, y, sample_weight, queue) and returns: self