class_docstr: A helper class that implements cutoff checks based on number of
  iterations and log likelihood.
  
  Accuracy cutoffs are also implemented, but they're almost never
  a good idea to use.
code: def __init__(self, cutoffs):
      self.cutoffs = cutoffs.copy()
      if "min_ll" in cutoffs:
          cutoffs["min_ll"] = -abs(cutoffs["min_ll"])
      if "min_lldelta" in cutoffs:
          cutoffs["min_lldelta"] = abs(cutoffs["min_lldelta"])
      self.ll = None
      self.acc = None
      self.iter = 1
  
file_path: nltk/nltk/classify/util.py
imports: import math
  import nltk.classify.util
  from nltk.util import LazyMap
label_desc: Use image node_id 1 to create a new CutoffChecker object  with example: obj = CutoffChecker(cutoffs)