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https://issues.apache.org/jira/browse/MADLIB-1351?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16909490#comment-16909490
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Frank McQuillan commented on MADLIB-1351:
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Let's try to find out why a final perplexity computation is done, and why it is
different from the last one in the array. Then we can perhaps come up with an
answer to your question.
> Add stopping criteria on perplexity to LDA
> ------------------------------------------
>
> Key: MADLIB-1351
> URL: https://issues.apache.org/jira/browse/MADLIB-1351
> Project: Apache MADlib
> Issue Type: Improvement
> Components: Module: Parallel Latent Dirichlet Allocation
> Reporter: Frank McQuillan
> Assignee: Himanshu Pandey
> Priority: Major
> Fix For: v1.17
>
>
> In LDA
> http://madlib.apache.org/docs/latest/group__grp__lda.html
> make stopping criteria on perplexity rather than just number of iterations.
> Suggested approach is to do what scikit-learn does
> https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.LatentDirichletAllocation.html
> evaluate_every : int, optional (default=0)
> How often to evaluate perplexity. Set it to 0 or negative number to not
> evaluate perplexity in training at all. Evaluating perplexity can help you
> check convergence in training process, but it will also increase total
> training time. Evaluating perplexity in every iteration might increase
> training time up to two-fold.
> perplexity_tol : float, optional (default=1e-1)
> Perplexity tolerance to stop iterating. Only used when evaluate_every is
> greater than 0.
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