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From "Apache Spark (Jira)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-36481) Expose LogisticRegression.setInitialModel
Date Wed, 11 Aug 2021 16:02:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-36481?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17397445#comment-17397445
] 

Apache Spark commented on SPARK-36481:
--------------------------------------

User 'srowen' has created a pull request for this issue:
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
>
> 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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