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https://issues.apache.org/jira/browse/SPARK-1405?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14221505#comment-14221505
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Debasish Das edited comment on SPARK-1405 at 11/21/14 10:28 PM:
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[~witgo] where can I access your dataset ? I got the NIPS dataset from Pedro
but here the runtimes reported are on a different dataset...also should we use
the same accuracy measure that Pedro is using ?
was (Author: debasish83):
[~witgo] where can I access your dataset ? I got the NIPS dataset from Pedro
but here the runtimes reported are on a different dataset...also should be use
the same accuracy measure that Pedro is using...
> parallel Latent Dirichlet Allocation (LDA) atop of spark in MLlib
> -----------------------------------------------------------------
>
> Key: SPARK-1405
> URL: https://issues.apache.org/jira/browse/SPARK-1405
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: Xusen Yin
> Assignee: Guoqiang Li
> Priority: Critical
> Labels: features
> Attachments: performance_comparison.png
>
> Original Estimate: 336h
> Remaining Estimate: 336h
>
> Latent Dirichlet Allocation (a.k.a. LDA) is a topic model which extracts
> topics from text corpus. Different with current machine learning algorithms
> in MLlib, instead of using optimization algorithms such as gradient desent,
> LDA uses expectation algorithms such as Gibbs sampling.
> In this PR, I prepare a LDA implementation based on Gibbs sampling, with a
> wholeTextFiles API (solved yet), a word segmentation (import from Lucene),
> and a Gibbs sampling core.
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