Extract Topic form Data (LDA) operator and optimize hyperparameter settings
I am working on a text mining using the Extract Topic from Data(LDA) operator and i am finding difficult understanding how to use the optimize hyperparameter setting?
Specifically the "Optimize interval for hyperparameter" and " iterations" and how they affect the results
i am currenly using the default alpha and beta heuristics. what is the effect of changing these values?
Specifically the "Optimize interval for hyperparameter" and " iterations" and how they affect the results
i am currenly using the default alpha and beta heuristics. what is the effect of changing these values?
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Altair EmployeeWow, @jwpfau. I didn't know that you as an engineer are so much into DS. Thats of course great!
Optimize interval for hyperparameter defines the number of iterations between hyperparameter optimizations, if you do this too often (low value) you might end up with instabilities due to alpha hyperparameters going to zero.
α influences the number of topics per document
β influences the number of words per topic
If you want to have some more sound knowledge about LDA:
- https://ai.stanford.edu/~ang/papers/jair03-lda.pdf
- http://videolectures.net/mlss09uk_blei_tm/
Or maybe @mschmitz can correct me