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.
class_docstr_tok: ["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","."]
docstr: Check whether this classifier can handle the data characteristics.
  
  Parameters
  ----------
  X_metadata : dict with metadata for X returned by datatypes.check_is_scitype
  
  Raises
  ------
  ValueError if the capabilities in self._tags do not handle the data.
docstr_tok: ["Check","whether","this","classifier","can","handle","the","data","characteristics",".","Parameters","--","--","--","--","--","X_metadata",":","dict","with","metadata","for","X","returned","by","datatypes.check_is_scitype","Raises","--","--","--","ValueError","if","the","capabilities","in","self._tags","do","not","handle","the","data","."]
code: def _check_capabilities(self, X_metadata):
      """Check whether this classifier can handle the data characteristics.
  
      Parameters
      ----------
      X_metadata : dict with metadata for X returned by datatypes.check_is_scitype
  
      Raises
      ------
      ValueError if the capabilities in self._tags do not handle the data.
      """
      _check_capabilities = BaseClassifier._check_capabilities
      return _check_capabilities(self, X_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 21 for calling the BaseEarlyClassifier obj's underlying member method code with example usage: obj._check_capabilities(X_metadata) and returns: _check_capabilities