class_docstr: Abstract base class for time series regressors.
  
  The base regressor specifies the methods and method signatures that all
  regressors have to implement. Attributes with a underscore suffix are set in the
  method fit.
  
  Parameters
  ----------
  fit_time_           : integer, time (in milliseconds) for fit to run.
  _class_dictionary   : dictionary mapping classes_ onto integers 0...n_classes_-1.
  _threads_to_use     : number of threads to use in fit as determined by n_jobs.
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code: def __init__(self):
      self.fit_time_ = 0
      self._class_dictionary = {}
      self._threads_to_use = 1
      self._X_metadata = {}
  
      # required for compatibility with some sklearn interfaces
      # i.e. CalibratedRegressorCV
      self._estimator_type = "regressor"
      self._is_vectorized = False
      self._is_timed = False
      self._converter_store_y = {}
  
      super().__init__()
  
file_path: sktime/sktime/regression/base.py
imports: import time
  import numpy
  from sktime.base import BasePanelMixin
  from sktime.datatypes import VectorizedDF
  from sktime.utils.sklearn import is_sklearn_transformer
  from sktime.utils.validation import check_n_jobs
label_desc: Use image node_id 1 to create a new BaseRegressor object from inherited base classes: BasePanelMixin with example: obj = BaseRegressor()