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I followed gensim's Core Tutorial and build an LSA Classification, topic modeling and Document Similarity model for newsgroups dataset.

My code is available here.

I need help with below 3 concepts.

  1. Topic Classification: I get only 50% accuracy with KNN algo.
  2. Topic Modeling: The words highlighted for each of the 20 topics doesnt stand out.
  3. Document Similarity: I wrote a small test code to find that document similarity also doesnt produce great results.

I am going to follow up it with other best models like LDA. However I am eager to know if I can improve my current LSA model. Any help here, would be really appreciable. Thanks!!

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    $\begingroup$ I’m voting to close this question because Code Review is off topic for this site. $\endgroup$
    – Ethan
    Commented Jun 17, 2021 at 18:18
  • $\begingroup$ Fine. If my post falls under Code Review, it can be closed. However the code and dataset is publicly available (from gensim and sklearn), I just pulled their code and thought of having a conversation around LSA instead of asking questions in many different posts. $\endgroup$
    – Bala
    Commented Jun 18, 2021 at 1:07

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