potential Doc2Vec feature: reverse inference, to synthesize doc/summary words #2459
Labels
difficulty medium
Medium issue: required good gensim understanding & python skills
feature
Issue described a new feature
good first issue
Issue for new contributors (not required gensim understanding + very simple)
Hacktoberfest
Issues marked for hacktoberfest
wishlist
Feature request
Motivated by the SO question: https://stackoverflow.com/questions/55768598/interpret-the-doc2vec-vectors-clusters-representation/55779049#55779049
Doc2Vec
could plausibly have a function that's reverse-inference: take a doc-vector, return a (ranked) list of words most-predicted by that input vector. It'd work highly analogously toWord2Vec.predict_output_word()
. Such a list of words might be useful as a sort-of summary or label for a doc-vector.The text was updated successfully, but these errors were encountered: