[jira] [Assigned] (SPARK-29691) Estimator fit method fails to copy params (in PySpark)

["Bryan Cutler (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-29691?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Bryan Cutler reassigned SPARK-29691:
------------------------------------

    Assignee: John Bauer

> Estimator fit method fails to copy params (in PySpark)
> ------------------------------------------------------
>
>                 Key: SPARK-29691
>                 URL: https://issues.apache.org/jira/browse/SPARK-29691
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 2.4.4
>            Reporter: John Bauer
>            Assignee: John Bauer
>            Priority: Minor
>             Fix For: 3.0.0
>
>
> Estimator `fit` method is supposed to copy a dictionary of params, overwriting the estimator's previous values, before fitting the model. However, the parameter values are not updated.  This was observed in PySpark, but may be present in the Java objects, as the PySpark code appears to be functioning correctly.   (The copy method that interacts with Java is actually implemented in Params.)
> For example, this prints
> Before: 0.8
> After: 0.8
> but After should be 0.75
> {code:python}
> from pyspark.ml.classification import LogisticRegression
> # Load training data
> training = spark \
>     .read \
>     .format("libsvm") \
>     .load("data/mllib/sample_multiclass_classification_data.txt")
> lr = LogisticRegression(maxIter=10, regParam=0.3, elasticNetParam=0.8)
> print("Before:", lr.getOrDefault("elasticNetParam"))
> # Fit the model, but with an updated parameter setting:
> lrModel = lr.fit(training, params={"elasticNetParam" : 0.75})
> print("After:", lr.getOrDefault("elasticNetParam"))
> {code}



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