Hi Christian.
Can you provide the data and code to reproduce?
Best,
Andy
On 01/26/2016 08:21 AM, Rockenkamm, Christian wrote:
Hallo,
I have question concerning the Latent Dirichlet Allocation. The
results I get from using it are a bit confusing.
At first I use about 3000 documents. In the preparation with the
CountVectorizrt I use the following parameters : max_df=0.95 and
min_df=0.05.
For the LDA fit I use the bath learning method. For the other
parameters I have tried many different values. However regardless of
which configuration I used, I face one common problem. I get topics
that are never used in any of the docs and said topics all show the
same structure (topic-word-distribution). I even tried gensim with the
same configuration as scikit, yet I still encountered this problem. I
also tried lowering the number of topics in the model, but this did
not lead to the expected results either. For 100 topics, 20-27 were
still affected by this problem, for 50 topics, there were still 2-8 of
them being affected, depending on the parameter setting.
Does anybody have an idea as to what might be causing this problem and
how to resolve it?
Best regards,
Christian Rockenkamm
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