How can I find what words are in each topic after applying LDA on text ?
Sanju
New Altair Community Member
Hi all,
I only see the top 5 words, but I can't find what other words in each topic.
Thanks
Sanjay
LDA Model
LDA Model with 20 topics alphaSum = 2.0285924067154273 beta = 0.019139372553800438 Topic 0 tokens=345657.0000 document_entropy=8.0896 word-length=7.4000 coherence=-10.0817 uniform_dist=3.8276 corpus_dist=1.2224 eff_num_words=739.9272 token-doc-diff=0.0178 rank_1_docs=0.1799 allocation_ratio=0.0869 allocation_count=0.1734 exclusivity=0.2313 health word-length=6.0000 coherence=0.0000 uniform_dist=0.0898 corpus_dist=0.0385 token-doc-diff=0.0130 exclusivity=0.8054 companies word-length=9.0000 coherence=-1.1568 uniform_dist=0.0523 corpus_dist=0.0069 token-doc-diff=0.0000 exclusivity=0.1182 startups word-length=8.0000 coherence=-0.9839 uniform_dist=0.0466 corpus_dist=0.0054 token-doc-diff=0.0023 exclusivity=0.1031 company word-length=7.0000 coherence=-1.1837 uniform_dist=0.0445 corpus_dist=-0.0013 token-doc-diff=0.0014 exclusivity=0.0417 startup word-length=7.0000 coherence=-1.0639 uniform_dist=0.0406 corpus_dist=0.0039 token-doc-diff=0.0011 exclusivity=0.0882 Topic 1 tokens=852784.0000 document_entropy=9.4027 word-length=5.6000 coherence=-9.7164 uniform_dist=4.4613 corpus_dist=0.8509 eff_num_words=302.2245 token-doc-diff=0.0012 rank_1_docs=0.1414 allocation_ratio=0.0766 allocation_count=0.1608 exclusivity=0.2635 apps word-length=4.0000 coherence=0.0000 uniform_dist=0.2079 corpus_dist=0.0497 token-doc-diff=0.0002 exclusivity=0.3843 users word-length=5.0000 coherence=-0.5399 uniform_dist=0.1801 corpus_dist=0.0321 token-doc-diff=0.0000 exclusivity=0.2216 mobile word-length=6.0000 coherence=-0.6889 uniform_dist=0.1485 corpus_dist=0.0255 token-doc-diff=0.0000 exclusivity=0.1904 google word-length=6.0000 coherence=-1.3039 uniform_dist=0.0879 corpus_dist=0.0172 token-doc-diff=0.0002 exclusivity=0.2262 android word-length=7.0000 coherence=-1.1189 uniform_dist=0.0648 corpus_dist=0.0148 token-doc-diff=0.0008 exclusivity=0.2949 Topic 2 tokens=726725.0000 document_entropy=9.5265 word-length=7.0000 coherence=-7.0986 uniform_dist=4.7579 corpus_dist=1.1700 eff_num_words=202.4635 token-doc-diff=0.0005 rank_1_docs=0.0950 allocation_ratio=0.0282 allocation_count=0.1139 exclusivity=0.4547 million word-length=7.0000 coherence=0.0000 uniform_dist=0.2162 corpus_dist=0.0471 token-doc-diff=0.0002 exclusivity=0.2991 company word-length=7.0000 coherence=-0.5201 uniform_dist=0.1916 corpus_dist=0.0268 token-doc-diff=0.0001 exclusivity=0.1506 funding word-length=7.0000 coherence=-0.5500 uniform_dist=0.1620 corpus_dist=0.0522 token-doc-diff=0.0001 exclusivity=0.7814 startup word-length=7.0000 coherence=-0.7616 uniform_dist=0.1340 corpus_dist=0.0297 token-doc-diff=0.0001 exclusivity=0.2514 capital word-length=7.0000 coherence=-0.8565 uniform_dist=0.1161 corpus_dist=0.03
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Best Answer
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HI @Sanju ,
this makes not that much sense. All Words are connected to all topics a bit. That's the nature of the algorithm. It's a one-to-many relationship. So you need to define a cutoff.
BR,
Martin5
Altair EmployeeAnswers
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Hi @Sanju
Have you try to modify the "top words per topics" parameter of the operator ?
Hope it helps,
Regards,
Lionel0 -
HI @Sanju ,
this makes not that much sense. All Words are connected to all topics a bit. That's the nature of the algorithm. It's a one-to-many relationship. So you need to define a cutoff.
BR,
Martin5
