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https://issues.apache.org/jira/browse/MADLIB-1352?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Frank McQuillan updated MADLIB-1352:
------------------------------------
    Fix Version/s:     (was: v1.18.0)
                   v2.0

>  Add warm start to LDA
> ----------------------
>
>                 Key: MADLIB-1352
>                 URL: https://issues.apache.org/jira/browse/MADLIB-1352
>             Project: Apache MADlib
>          Issue Type: New Feature
>          Components: Module: Parallel Latent Dirichlet Allocation
>            Reporter: Frank McQuillan
>            Assignee: Himanshu Pandey
>            Priority: Major
>             Fix For: v2.0
>
>
> In LDA 
> http://madlib.apache.org/docs/latest/group__grp__lda.html
> implement warm start so can pick up from where you left off in the last 
> training.
> I would suggest we model this on the warm start implemented in MLP
> http://madlib.apache.org/docs/latest/group__grp__nn.html
> since it will be the same general idea for LDA.
> The LDA interface will be:
> {code}
> lda_train( data_table,
>            model_table,
>            output_data_table,
>            voc_size,
>            topic_num,
>            iter_num,
>            alpha,
>            beta,
>            evaluate_every,
>            perplexity_tol,
>            warm_start               -- new param
>          )
> warm_start (optional)
> BOOLEAN, default: FALSE. Initialize weights with the coefficients from the 
> last call of the training function. If set to true, weights will be 
> initialized from the model_table generated by the previous run.  Note that 
> parameters voc_size and  topic_num must remain constant between calls when 
> warm_start is used.  Other parameters can be changed for the warm start run.
> {code}
> Open questions
> 1) Validate this statement:  
> {code}
> Note that parameters voc_size and  topic_num must remain constant between 
> calls when warm_start is used.  Other parameters can be changed for the warm 
> start run.
> {code}
> Notes
> 1) Depending on open question #1 above, do validation checks on user input to 
> ensure that user does not change any parameter that they are not allowed to 
> change from the previous run.



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