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: Check whether input X and y are valid formats with minimum data.
  
  Raises a ValueError if the input is not valid.
  
  Parameters
  ----------
  X : check whether conformant with any sktime Panel mtype specification
  y : check whether a pd.Series or np.array
  enforce_min_instances : int, optional (default=1)
      check there are a minimum number of instances.
  return_metadata : bool, str, or list of str
      metadata fields to return with X_metadata, input to check_is_scitype
  
  Returns
  -------
  metadata : dict with metadata for X returned by datatypes.check_is_scitype
  
  Raises
  ------
  ValueError
      If y or X is invalid input data type, or there is not enough data
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code: def _check_input(
      self, X, y=None, enforce_min_instances=1, return_metadata=True
  ):
      """Check whether input X and y are valid formats with minimum data.
  
      Raises a ValueError if the input is not valid.
  
      Parameters
      ----------
      X : check whether conformant with any sktime Panel mtype specification
      y : check whether a pd.Series or np.array
      enforce_min_instances : int, optional (default=1)
          check there are a minimum number of instances.
      return_metadata : bool, str, or list of str
          metadata fields to return with X_metadata, input to check_is_scitype
  
      Returns
      -------
      metadata : dict with metadata for X returned by datatypes.check_is_scitype
  
      Raises
      ------
      ValueError
          If y or X is invalid input data type, or there is not enough data
      """
      _check_input = BaseClassifier._check_input
      return _check_input(
          self, X, y, enforce_min_instances, return_metadata
      )
  
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 24 for calling the BaseEarlyClassifier obj's underlying member method code with example usage: obj._check_input(X, y, enforce_min_instances, return_metadata) and returns: _check_input