code: def radius_neighbors(
      self,
      X=None,
      radius=None,
      return_distance=True,
      sort_results=False,
  ):
      _onedal_estimator = getattr(self, "_onedal_estimator", None)
  
      if (
          _onedal_estimator is not None
          or getattr(self, "_tree", 0) is None
          and self._fit_method == "kd_tree"
      ):
          if sklearn_check_version("0.24"):
              sklearn_NearestNeighbors.fit(
                  self, self._fit_X, getattr(self, "_y", None)
              )
          else:
              sklearn_NearestNeighbors.fit(self, self._fit_X)
      if sklearn_check_version("0.22"):
          result = sklearn_NearestNeighbors.radius_neighbors(
              self, X, radius, return_distance, sort_results
          )
      else:
          result = sklearn_NearestNeighbors.radius_neighbors(
              self, X, radius, return_distance
          )
  
      return result
  
imports: import warnings
  from sklearn.neighbors._ball_tree import BallTree
  from sklearn.neighbors._base import NeighborsBase
  from sklearn.neighbors._kd_tree import KDTree
  from daal4py.sklearn._utils import control_n_jobs, run_with_n_jobs, sklearn_check_version
  import numpy
  from sklearn.neighbors._base import VALID_METRICS
  from sklearn.neighbors._regression import KNeighborsRegressor
  from sklearn.neighbors._unsupervised import NearestNeighbors
  from sklearn.utils.validation import _deprecate_positional_args, check_is_fitted
  from onedal.neighbors import KNeighborsRegressor
  from onedal.utils import _check_array, _num_features, _num_samples
  from .._device_offload import dispatch, wrap_output_data
  from .common import KNeighborsDispatchingBase
label_desc: Use image node_id 4 for calling the KNeighborsRegressor obj's underlying member method code with example usage: obj.radius_neighbors(X, radius, return_distance, sort_results) and returns: result