Created
May 6, 2019 13:01
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Cosine Similarity
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| def cosine_distance_wordembedding_method(s1, s2): | |
| import scipy | |
| vector_1 = np.mean([model[word] for word in preprocess(s1)],axis=0) | |
| vector_2 = np.mean([model[word] for word in preprocess(s2)],axis=0) | |
| cosine = scipy.spatial.distance.cosine(vector_1, vector_2) | |
| print('Word Embedding method with a cosine distance asses that our two sentences are similar to',round((1-cosine)*100,2),'%') |
why is similarity calculated as (1 - cosine) and not cosine?
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hi.
which modules i should import to run this code