gensim.models.Doc2Vec.n_similarity¶

Doc2Vec.n_similarity(ws1, ws2)¶

Compute cosine similarity between two sets of words.

Example:

>>> trained_model.n_similarity(['sushi', 'shop'], ['japanese', 'restaurant'])
0.61540466561049689

>>> trained_model.n_similarity(['restaurant', 'japanese'], ['japanese', 'restaurant'])
1.0000000000000004

>>> trained_model.n_similarity(['sushi'], ['restaurant']) == trained_model.similarity('sushi', 'restaurant')
True