class_docstr: Base time series forest classifier.
class_docstr_tok: ["Base","time","series","forest","classifier","."]
docstr: Access first parameter in self, self inheriting from sklearn BaseForest.
  
  The attribute was renamed from base_estimator to estimator in sklearn 1.2.0.
docstr_tok: ["Access","first","parameter","in","self",",","self","inheriting","from","sklearn","BaseForest",".","The","attribute","was","renamed","from","base_estimator","to","estimator","in","sklearn","1.2.0","."]
code: def _estimator(self):
      """Access first parameter in self, self inheriting from sklearn BaseForest.
  
      The attribute was renamed from base_estimator to estimator in sklearn 1.2.0.
      """
      import sklearn
      from packaging.specifiers import SpecifierSet
  
      sklearn_version = sklearn.__version__
  
      if sklearn_version in SpecifierSet(">=1.2.0"):
          return self.estimator
      else:
          return self.base_estimator
  
file_path: sktime/sktime/series_as_features/base/estimators/interval_based/_tsf.py
imports: import math
  from typing import Optional
  import numpy
  from joblib import Parallel, delayed
  from numpy.random import RandomState
  from sklearn.utils.multiclass import class_distribution
  from sklearn.utils.validation import check_random_state
  from sktime.base._base import _clone_estimator
  from sktime.utils.slope_and_trend import _slope
  from sktime.utils.validation import check_n_jobs
label_desc: Use image node_id 2 for calling the BaseTimeSeriesForest obj's underlying member method code with example usage: obj._estimator() and returns: self, self