class_docstr: Handles parameter management for estimators composed of named estimators.
  
  Partly adapted from sklearn utils.metaestimator.py.
docstr: Check if the object is composite.
  
  A composite object is an object which contains objects, as parameters.
  Called on an instance, since this may differ by instance.
  
  Returns
  -------
  composite: bool, whether self contains a parameter which is BaseObject
docstr_tok: ["Check","if","the","object","is","composite",".","A","composite","object","is","an","object","which","contains","objects",",","as","parameters",".","Called","on","an","instance",",","since","this","may","differ","by","instance",".","Returns","--","--","--","-","composite",":","bool",",","whether","self","contains","a","parameter","which","is","BaseObject"]
code: def is_composite(self):
      """Check if the object is composite.
  
      A composite object is an object which contains objects, as parameters.
      Called on an instance, since this may differ by instance.
  
      Returns
      -------
      composite: bool, whether self contains a parameter which is BaseObject
      """
      # children of this class are always composite
      return True
  
imports: from inspect import isclass
  import numpy
  import pandas
  from sktime.base import BaseEstimator
label_desc: Use image node_id 4 for calling the _HeterogenousMetaEstimator obj's underlying member method code with example usage: obj.is_composite() and returns: True