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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docstr: Predicts labels for sequences in X.
  
  Abstract method, must be implemented.
  
  Parameters
  ----------
  X : guaranteed to be of a type in self.get_tag("X_inner_mtype")
      if self.get_tag("X_inner_mtype") = "numpy3D":
          3D np.ndarray of shape = [n_instances, n_dimensions, series_length]
      if self.get_tag("X_inner_mtype") = "nested_univ":
          pd.DataFrame with each column a dimension, each cell a pd.Series
      for list of other mtypes, see datatypes.SCITYPE_REGISTER
      for specifications, see examples/AA_datatypes_and_datasets.ipynb
  
  Returns
  -------
  y : 1D np.array of float, of shape [n_instances] - predicted regression labels
      indices correspond to instance indices in X
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code: def _predict(self, X) -> np.ndarray:
      """Predicts labels for sequences in X.
  
      Abstract method, must be implemented.
  
      Parameters
      ----------
      X : guaranteed to be of a type in self.get_tag("X_inner_mtype")
          if self.get_tag("X_inner_mtype") = "numpy3D":
              3D np.ndarray of shape = [n_instances, n_dimensions, series_length]
          if self.get_tag("X_inner_mtype") = "nested_univ":
              pd.DataFrame with each column a dimension, each cell a pd.Series
          for list of other mtypes, see datatypes.SCITYPE_REGISTER
          for specifications, see examples/AA_datatypes_and_datasets.ipynb
  
      Returns
      -------
      y : 1D np.array of float, of shape [n_instances] - predicted regression labels
          indices correspond to instance indices in X
      """
      raise NotImplementedError("abstract method")
  
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 7 for calling the BaseRegressor obj's underlying member method code with example usage: obj._predict(X) without return types