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Fix min_count handling in phrases detection using npmi #2072

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Jul 31, 2018
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15 changes: 10 additions & 5 deletions gensim/models/phrases.py
Original file line number Diff line number Diff line change
@@ -668,7 +668,7 @@ def npmi_scorer(worda_count, wordb_count, bigram_count, len_vocab, min_count, co
len_vocab : int
Not used.
min_count: int
Not used.
Ignore all bigrams with total collected count lower than this value.
corpus_word_count : int
Total number of words in the corpus.

@@ -678,10 +678,15 @@ def npmi_scorer(worda_count, wordb_count, bigram_count, len_vocab, min_count, co
where :math:`prob(word) = \\frac{word\_count}{corpus\_word\_count}`

"""
pa = worda_count / corpus_word_count
pb = wordb_count / corpus_word_count
pab = bigram_count / corpus_word_count
return log(pab / (pa * pb)) / -log(pab)
if bigram_count >= min_count:
pa = worda_count / corpus_word_count
pb = wordb_count / corpus_word_count
pab = bigram_count / corpus_word_count
return log(pab / (pa * pb)) / -log(pab)
else:
# Return -infinity to make sure that no phrases will be created
# from bigrams less frequent than min_count
return float('-inf')


def pseudocorpus(source_vocab, sep, common_terms=frozenset()):