[
https://issues.apache.org/jira/browse/SPARK-5556?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14520000#comment-14520000
]
Pedro Rodriguez commented on SPARK-5556:
----------------------------------------
What are thoughts on implementation?It looks like LightLDA converges faster and
takes more memory, but FastLDA is slightly faster. Could you give a good
summary of comparing the different algorithms [~gq]? I went through the data
and plots, but some interpretation would be great.
How should we move forward on choosing an implementation? It makes more sense
to decide on something, then work on merging that choice rather than preparing
multiple choices. On my Gibbs implementation, I am working on the assumption
that algorithmically it is the same as [~gq]'s and should perform comparably.
> Latent Dirichlet Allocation (LDA) using Gibbs sampler
> ------------------------------------------------------
>
> Key: SPARK-5556
> URL: https://issues.apache.org/jira/browse/SPARK-5556
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: Guoqiang Li
> Assignee: Pedro Rodriguez
> Attachments: LDA_test.xlsx, spark-summit.pptx
>
>
--
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
