class_docstr: Abstract base class for early time series classifiers.
  
  The base classifier specifies the methods and method signatures that all
  early classifiers have to implement. Attributes with an underscore suffix are set in
  the method fit.
  
  Parameters
  ----------
  classes_            : ndarray of class labels, possibly strings
  n_classes_          : integer, number of classes (length of classes_)
  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.
  state_info          : An array containing the state info for each decision in X.
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docstr: Input checks, capability checks, repeated in all predict/score methods.
  
  Parameters
  ----------
  X : any object (to check/convert)
      should be of a supported Panel mtype or 2D numpy.ndarray
  
  Returns
  -------
  X: an object of a supported Panel mtype, numpy3D if X was a 2D numpy.ndarray
  
  Raises
  ------
  ValueError if X is of invalid input data type, or there is not enough data
  ValueError if the capabilities in self._tags do not handle the data.
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code: def _check_convert_X_for_predict(self, X):
      """Input checks, capability checks, repeated in all predict/score methods.
  
      Parameters
      ----------
      X : any object (to check/convert)
          should be of a supported Panel mtype or 2D numpy.ndarray
  
      Returns
      -------
      X: an object of a supported Panel mtype, numpy3D if X was a 2D numpy.ndarray
  
      Raises
      ------
      ValueError if X is of invalid input data type, or there is not enough data
      ValueError if the capabilities in self._tags do not handle the data.
      """
      _check_convert_X_for_predict = (
          BaseClassifier._check_convert_X_for_predict
      )
      return _check_convert_X_for_predict(self, X)
  
imports: from abc import ABC, abstractmethod
  from typing import Tuple
  import numpy
  from sktime.base import BaseEstimator
  from sktime.classification import BaseClassifier
label_desc: Use image node_id 20 for calling the BaseEarlyClassifier obj's underlying member method code with example usage: obj._check_convert_X_for_predict(X) and returns: _check_convert_X_for_predict