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