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Mohamed Baddar commented on SPARK-9134: --------------------------------------- [~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. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org