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https://issues.apache.org/jira/browse/SPARK-9245?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14702155#comment-14702155
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Meihua Wu commented on SPARK-9245:
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[~josephkb] Thank you for clarifying my question. I was originally planning to
work on this but I just got too busy last week. I could help reviewing though.
> DistributedLDAModel predict top topic per doc-term instance
> -----------------------------------------------------------
>
> Key: SPARK-9245
> URL: https://issues.apache.org/jira/browse/SPARK-9245
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: Joseph K. Bradley
> Original Estimate: 48h
> Remaining Estimate: 48h
>
> For each (document, term) pair, return top topic. Note that instances of
> (doc, term) pairs within a document (a.k.a. "tokens") are exchangeable, so we
> should provide an estimate per document-term, rather than per token.
> Synopsis for DistributedLDAModel:
> {code}
> /** @return RDD of (doc ID, vector of top topic index for each term) */
> def topTopicAssignments: RDD[(Long, Vector)]
> {code}
> Note that using Vector will let us have a sparse encoding which is
> Java-friendly.
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