code: def check_classification_parameters(
      y, y_hat, protected, privileged, verbose
  ):
      if list(np.unique(y)) != [0, 1]:
          raise ParameterCheckError("model must predict binary target")
  
      if not 0 <= y_hat.all() <= 1:
          raise ParameterCheckError(
              "y_hat must have probabilistic output between 0 and 1"
          )
  
      return
  
imports: import numpy
  from .._basics.exceptions import ParameterCheckError
  from ..._explainer import helper
label_desc: Use image node_id 2 for calling a global function with example usage: check_classification_parameters(y, y_hat, protected, privileged, verbose) without return types