[jira] [Resolved] (SPARK-36481) Expose LogisticRegression.setInitialModel

["DB Tsai (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-36481?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

DB Tsai resolved SPARK-36481.
-----------------------------
    Fix Version/s: 3.3.0
       Resolution: Fixed

Issue resolved by pull request 33710
[https://github.com/apache/spark/pull/33710]

> Expose LogisticRegression.setInitialModel
> -----------------------------------------
>
>                 Key: SPARK-36481
>                 URL: https://issues.apache.org/jira/browse/SPARK-36481
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>    Affects Versions: 3.2.0
>            Reporter: Sean R. Owen
>            Assignee: Sean R. Owen
>            Priority: Minor
>             Fix For: 3.3.0
>
>
> Several Spark ML components already allow setting of an initial model, including KMeans, LogisticRegression, and GaussianMixture. This is useful to begin training from a known reasonably good model.
> However, the method in LogisticRegression is private to Spark. I don't see a good reason why it should be as the others in KMeans et al are not.
> None of these are exposed in Pyspark, which I don't necessarily want to question or deal with now; there are other places one could arguably set an initial model too, but, here just interested in exposing the existing, tested functionality to callers.



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