'Return `top_n` bigram features (using `assoc_measure`).
Note that this method is based on bigram collocations measures, and not
on simple bigram frequency.
:param documents: a list (or iterable) of tokens.
:param top_n: number of best words/tokens to use, sorted by association
measure.
:param assoc_measure: bigram association measure to use as score function.
:param min_freq: the minimum number of occurrencies of bigrams to take
into consideration.
:return: `top_n` ngrams scored by the given association measure.'

def bigram_collocation_feats(self, documents, top_n=None, min_freq=3, assoc_measure=BigramAssocMeasures.pmi):

    finder = BigramCollocationFinder.from_documents(documents)
    finder.apply_freq_filter(min_freq)
    return finder.nbest(assoc_measure, top_n)
