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https://issues.apache.org/jira/browse/MADLIB-1160?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Frank McQuillan closed MADLIB-1160.
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> Usability changes for LDA
> -------------------------
>
> Key: MADLIB-1160
> URL: https://issues.apache.org/jira/browse/MADLIB-1160
> Project: Apache MADlib
> Issue Type: Improvement
> Components: Module: Utilities
> Reporter: Frank McQuillan
> Assignee: Jingyi Mei
> Priority: Minor
> Fix For: v1.14
>
>
> Context
> Please see this thread from the user mailing list
>
> [http://mail-archives.apache.org/mod_mbox/incubator-madlib-user/201709.mbox/%3CCA%2B9JwyW78-aoe-NCQZc_iMuqW6SpKXs0H4JeTMfo3b-G4cxm0w%40mail.gmail.com%3E]
> Tasks
> 1) Term frequency
> [http://madlib.apache.org/docs/latest/group__grp__text__utilities.html]
> and LDA
> [http://madlib.apache.org/docs/latest/group__grp__lda.html]
> should both creates indexes that start at 1, to make them consistent with
> other MADlib modules. One or both of these currently create indexes starting
> at 0.
> 2) In the output_data_table *topic_assignment* is a dense vector but *words*
> is a sparse vector (svec).
> We should change *topic_assignment* to be a sparse vector to be consistent.
> Note: the reason sparse vectors were used in the first place (I think) is to
> keep the model state as small as possible, so it is preferred to dense format
> in this case., although svecs are a bit harder to work with. We have hit the
> Postgres 1GB field limit size in some use cases.
> 3) The user docs could also use some cleanup at the same time. E.g., helper
> functions are used in the examples but not described above.
> 4) The helper function `madlib.lda_get_topic_desc` should return top k words
> (and ties). It seems to returning the top k-1 words (and ties) now.
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