[
https://issues.apache.org/jira/browse/SPARK-20767?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen resolved SPARK-20767.
-------------------------------
Resolution: Duplicate
Let's roll this proposal into the existing issue
> The training continuation for saved LDA model
> ---------------------------------------------
>
> Key: SPARK-20767
> URL: https://issues.apache.org/jira/browse/SPARK-20767
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 2.1.1
> Reporter: Cezary Dendek
> Priority: Minor
>
> Current online implementation of the LDA model fit (OnlineLDAOptimizer) does
> not support the model update (ie. to account for the population/covariates
> drift) nor the continuation of model fitting in case of the insufficient
> number of iterations.
> Technical aspects:
> 1. The implementation of LDA fitting does not currently allow the
> coefficients pre-setting (private setter), as noted by a comment in the
> source code of OnlineLDAOptimizer.setLambda: "This is only used for testing
> now. In the future, it can help support training stop/resume".
> 2. The lambda matrix is always randomly initialized by the optimizer, which
> needs fixing for preset lambda matrix.
> The adaptation of the classes by the user is not possible due to protected
> setters & sealed / final classes.
--
This message was sent by Atlassian JIRA
(v6.3.15#6346)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
