class_docstr: Replaces a random covariate with an irrelevant variable.
code: def __init__(self, *args, **kwargs):
      super().__init__(*args, **kwargs)
      if "replaced_feature" not in kwargs:
          replaced_feature_index = np.random.randint(
              len(self.inference_features)
          )
          self.replaced_feature = self.inference_features[
              replaced_feature_index
          ]
      else:
          self.replaced_feature = kwargs["replaced_feature"]
  
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 1 to create a new SensitivityRandomReplace object from inherited base classes: Sensitivity with example: obj = SensitivityRandomReplace()