class_docstr: Abstract base class for all IBM models
class_docstr_tok: ["Abstract","base","class","for","all","IBM","models"]
code: def maximize_null_generation_probabilities(self, counts):
      p1_estimate = counts.p1 / (counts.p1 + counts.p0)
      p1_estimate = max(p1_estimate, IBMModel.MIN_PROB)
      # Clip p1 if it is too large, because p0 = 1 - p1 should not be
      # smaller than MIN_PROB
      self.p1 = min(p1_estimate, 1 - IBMModel.MIN_PROB)
  
imports: from bisect import insort_left
  from collections import defaultdict
  from copy import deepcopy
  from math import ceil
label_desc: Use image node_id 11 for calling the IBMModel obj's underlying member method code with example usage: obj.maximize_null_generation_probabilities(counts) without return types