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https://issues.apache.org/jira/browse/SPARK-5567?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14578595#comment-14578595
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yuhao yang commented on SPARK-5567:
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Hi Joseph, just to be clear. If we're using the MAP prediction you mentioned,
does it require "fold-in" Gibbs sampling（and convergence) in the prediction
process, or just straightforward summation?
I checked the implementation in
https://github.com/mimno/Mallet/blob/master/src/cc/mallet/topics/TopicInferencer.java#L81.
Is it something aligned with your idea?
> Add prediction methods to LDA
> -----------------------------
>
> Key: SPARK-5567
> URL: https://issues.apache.org/jira/browse/SPARK-5567
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.3.0
> Reporter: Joseph K. Bradley
>
> LDA currently supports prediction on the training set. E.g., you can call
> logLikelihood and topicDistributions to get that info for the training data.
> However, it should support the same functionality for new (test) documents.
> This will require inference but should be able to use the same code, with a
> few modification to keep the inferred topics fixed.
> Note: The API for these methods is already in the code but is commented out.
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