How to use Gensim Doc2vec infer_vector() for large DataFrame?
@gojomo: Thanks for the answer, but I tried inferring using both tokenized rows as well as raw strings, and got the same document vector.
Is there a way to know if the document vector which are getting created are meaningful or not?
I have created document vectors for a large corpus using Gensim's doc2vec.
sentences=gensim.models.doc2vec.TaggedLineDocument('file.csv')
model = gensim.models.doc2vec.Doc2Vec(sentences,size = 10, window = 800, min_count = 1, workers=40, iter=10, dm=0)
Now I am using Gensim's infer_vector() using those document vectors to create document vectors for another sample corpus
Eg: model.infer_vector('This is a string')
Is there a way to pass the entire DataFrame through infer_vector and get the output vectors for each line in the DataFrame?