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Meihua Wu commented on SPARK-9245: ---------------------------------- [~josephkb]: would like to confirm: (using notation Asuncion 2009), for doc `j` and term `w`, find the topic `k` such that gamma_wjk is maximized? > 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. -- 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