class_docstr: A tool for the finding and ranking of bigram collocations or other
  association measures. It is often useful to use from_words() rather than
  constructing an instance directly.
class_docstr_tok: ["A","tool","for","the","finding","and","ranking","of","bigram","collocations","or","other","association","measures",".","It","is","often","useful","to","use","from_words","(",")","rather","than","constructing","an","instance","directly","."]
docstr: Construct a BigramCollocationFinder, given FreqDists for
  appearances of words and (possibly non-contiguous) bigrams.
docstr_tok: ["Construct","a","BigramCollocationFinder",",","given","FreqDists","for","appearances","of","words","and","(","possibly","non-contiguous",")","bigrams","."]
code: def __init__(self, word_fd, bigram_fd, window_size=2):
      """Construct a BigramCollocationFinder, given FreqDists for
      appearances of words and (possibly non-contiguous) bigrams.
      """
      AbstractCollocationFinder.__init__(self, word_fd, bigram_fd)
      self.window_size = window_size
  
imports: import itertools
  from nltk.metrics import BigramAssocMeasures, ContingencyMeasures, QuadgramAssocMeasures, TrigramAssocMeasures
  from nltk.metrics.spearman import ranks_from_scores, spearman_correlation
  from nltk.probability import FreqDist
  from nltk.util import ngrams
label_desc: Use image node_id 1 to create a new BigramCollocationFinder object from inherited base classes: AbstractCollocationFinder with example: obj = BigramCollocationFinder(word_fd, bigram_fd, window_size)