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https://issues.apache.org/jira/browse/SPARK-9134?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15195217#comment-15195217
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Mohamed Baddar commented on SPARK-9134:
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[~josephkb] [~fliang] If no body working on that , and there is an interest in
that issue , can i start working on it ?
> LDA Asymmetric topic-word prior
> -------------------------------
>
> Key: SPARK-9134
> URL: https://issues.apache.org/jira/browse/SPARK-9134
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Reporter: Feynman Liang
>
> SPARK-8536 generalizes LDA to asymmetric document-topic priors, which
> [Wallach et al|http://dirichlet.net/pdf/wallach09rethinking.pdf] proposes
> offers greater utility in terms of asymmetric priors.
> However, [Stanford
> NLP|http://nlp.stanford.edu/software/tmt/tmt-0.2/scaladocs/scaladocs/edu/stanford/nlp/tmt/lda/LDA.html]
> also permits asymmetric priors on the topic-word prior. We should not
> support manually specifying the entire matrix (which has numTopics *
> vocabSize entries); rather we should follow Stanford NLP and take a single
> vector of length vocabSize for a prior over words and assume that all topics
> share this prior (e.g. replicate it numTopics times to get the topic-word
> prior matrix).
> We are leaving this as todo; any users who have a need for this feature
> should discuss on this JIRA.
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