class_docstr: A Sensitivity Check class to support Placebo Treatment, Irrelevant Additional Confounder
  and Subset validation refutation methods to verify causal inference.
  
  Reference: https://github.com/microsoft/dowhy/blob/master/dowhy/causal_refuters/
docstr: Return class object based on input method
  Args:
      method_name (list of str): a list of sensitivity analysis method
  Returns:
      (class): Sensitivy Class
docstr_tok: ["Return","class","object","based","on","input","method","Args",":","method_name","(","list","of","str",")",":","a","list","of","sensitivity","analysis","method","Returns",":","(","class",")",":","Sensitivy","Class"]
code: def get_class_object(method_name, *args, **kwargs):
      """Return class object based on input method
      Args:
          method_name (list of str): a list of sensitivity analysis method
      Returns:
          (class): Sensitivy Class
      """
  
      method_list = [
          "Placebo Treatment",
          "Random Cause",
          "Subset Data",
          "Random Replace",
          "Selection Bias",
      ]
      class_name = "Sensitivity" + method_name.replace(" ", "")
  
      try:
          getattr(
              import_module("causalml.metrics.sensitivity"), class_name
          )
          return getattr(
              import_module("causalml.metrics.sensitivity"), class_name
          )
      except AttributeError:
          raise AttributeError(
              "{} is not an existing method for sensitiviy analysis.".format(
                  method_name
              )
              + " Select one of {}".format(method_list)
          )
  
imports: import logging
  import numpy
  import pandas
  from collections import defaultdict
  import matplotlib.pyplot
  from importlib import import_module
label_desc: Use image node_id 4 for calling the Sensitivity obj's underlying member method code with example usage: obj.get_class_object(method_name) and returns: getattr