[jira] [Resolved] (SPARK-19216) LogisticRegressionModel is missing getThreshold()

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-19216?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-19216.
----------------------------------
    Resolution: Incomplete

> LogisticRegressionModel is missing getThreshold()
> -------------------------------------------------
>
>                 Key: SPARK-19216
>                 URL: https://issues.apache.org/jira/browse/SPARK-19216
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML, PySpark
>    Affects Versions: 2.1.0
>            Reporter: Nicholas Chammas
>            Priority: Minor
>              Labels: bulk-closed
>
> Say I just loaded a logistic regression model from storage. How do I check that model's threshold in PySpark? From what I can see, the only way to do that is to dip into the Java object:
> {code}
> model._java_obj.getThreshold())
> {code}
> It seems like PySpark's version of {{LogisticRegressionModel}} should include this method.
> Another issue is that it's not clear whether the threshold is for the raw prediction or the probability. Maybe it's obvious to machine learning practitioners, but I couldn't tell from reading the docs or skimming the code what the threshold was for exactly.



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