Take the 2-minute tour ×  Right now, I'm using LDA topic
modelling tool from the MALLET package to do some topic
detection on my documents. Everything's fine initially, I got 20
topics from it. However, when I try to infer new document using
the model, the result is kinda baffling.  For instance I
deliberately run my model over a document that I manually
created which contains nothing but keywords from one of the
topics "FLU", but the topic distributions I got was <0.1 for
every topic. I then try the same thing on one of the already
sampled document which has a high score of 0.7 for one of the
topics. Again the same thing happened.  Can someone give some
clue on the reason?  Tried asking on MALLET mailing list but
apparently no one has replied.  share|improve this question When
you say that you run your model over the document you created,
what exactly are you doing? Are you attempting to re-run the
inference portion of the LDA algorithm on the new document? If
so, your result would be expected behavior. It s