在vowpal wabbit中设置LDA模型的超参数

Question

I am a typical, regular, everyday Spark user. In Spark's LDA there are hyperparameters thats stands for

docConcentration : Hyperparameter for prior over documents' distributions over topics. Currently must be > 1, where larger values encourage smoother inferred distributions. topicConcentration : Hyperparameter for prior over topics' distributions over terms (words). Currently must be > 1, where larger values encourage smoother inferred distributions.

which corresponds to typically assigned in the literature $\\alpha$ and $\\beta$ parameters for which (and $k$ - number of topics) the log-likelihood function of the LDA model is optimized during the convergence process.

Does anyone know if there is any option to set such arguments/parameters prior in vowpal wabbit's LDA model?

Answer 1

Check this description of vw lda. ! I think the parameters mentioned on 13th slide might be the ones that you are looking for.