added function to get a coherence score #94
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Amine-OMRI
reviewed
Apr 15, 2021
| tokens = [tokenizer_(doc) for doc in cleaned_documents] | ||
| dictionary = corpora.Dictionary(tokens) | ||
| corpus = [dictionary.doc2bow(token) for token in tokens] | ||
| topic_words_ = [[words for words, _ in self.get_topic(topic)] for topic in range(len(set(topics))-1)] |
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topic_words_ = set([[words for words, _ in self.get_topic(topic)] for topic in range(len(set(topics))-1)])
use a set instead of a list to obtain unique words that will improve the NPMI score
Amine-OMRI
reviewed
Apr 15, 2021
| """ | ||
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| if coherence == None: | ||
| coherence = 'c_v' |
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def get_coherence_score(self, documents : List[str], coherence='c_v') -> float:
setting the defaul coherence to 'c_v'
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CoherenceModel uses gensim. Should I include gensim in the requirements?
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Following the latest issue : #90
I have added a function to calculate coherence scores in _bertopic.py