class_docstr: An untargeted attack on classification models which attempts to minimize
  the score of the correct label until it is no longer the predicted label.
  
  Args:
      target_max_score (float): If set, goal is to reduce model output to
          below this score. Otherwise, goal is to change the overall predicted
          class.
class_docstr_tok: ["An","untargeted","attack","on","classification","models","which","attempts","to","minimize","the","score","of","the","correct","label","until","it","is","no","longer","the","predicted","label",".","Args",":","target_max_score","(","float",")",":","If","set",",","goal","is","to","reduce","model","output","to","below","this","score",".","Otherwise",",","goal","is","to","change","the","overall","predicted","class","."]
code: def __init__(self, *args, target_max_score=None, **kwargs):
      self.target_max_score = target_max_score
      super().__init__(*args, **kwargs)
  
imports: from .classification_goal_function import ClassificationGoalFunction
label_desc: Use image node_id 1 to create a new UntargetedClassification object from inherited base classes: ClassificationGoalFunction with example: obj = UntargetedClassification()