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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2016/07/28 23:29:20 UTC

[jira] [Commented] (SPARK-16768) pyspark calls incorrect version of logistic regression

    [ https://issues.apache.org/jira/browse/SPARK-16768?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15398409#comment-15398409 ] 

Sean Owen commented on SPARK-16768:
-----------------------------------

That's spark.ml.LogisticRegression, right? there's no longer a separate LBFGS version in .ml. 

> pyspark calls incorrect version of logistic regression
> ------------------------------------------------------
>
>                 Key: SPARK-16768
>                 URL: https://issues.apache.org/jira/browse/SPARK-16768
>             Project: Spark
>          Issue Type: Bug
>          Components: MLlib, PySpark
>         Environment: Linux openSUSE Leap 42.1 Gnome
>            Reporter: Colin Beckingham
>             Fix For: 2.1.0
>
>
> PySpark call with Spark 1.6.2 "LogisticRegressionWithLBFGS.train()"  runs "treeAggregate at LBFGS.scala:218" but the same command in pyspark with Spark 2.1 runs "treeAggregate at LogisticRegression.scala:1092". This non-optimized version is much slower and produces a different answer from LBFGS.



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