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https://issues.apache.org/jira/browse/SPARK-5571?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14606159#comment-14606159
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Alok Singh commented on SPARK-5571:
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Since there is already Tokenizer class. We can assume other classes will be
made. so one I can assume that input is already tokenized, stemmed and stopword
removed.
> LDA should handle text as well
> ------------------------------
>
> Key: SPARK-5571
> URL: https://issues.apache.org/jira/browse/SPARK-5571
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.3.0
> Reporter: Joseph K. Bradley
>
> Latent Dirichlet Allocation (LDA) currently operates only on vectors of word
> counts. It should also supporting training and prediction using text
> (Strings).
> This plan is sketched in the [original LDA design
> doc|https://docs.google.com/document/d/1kSsDqTeZMEB94Bs4GTd0mvdAmduvZSSkpoSfn-seAzo/edit?usp=sharing].
> There should be:
> * runWithText() method which takes an RDD with a collection of Strings (bags
> of words). This will also index terms and compute a dictionary.
> * dictionary parameter for when LDA is run with word count vectors
> * prediction/feedback methods returning Strings (such as
> describeTopicsAsStrings, which is commented out in LDA currently)
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