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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-17792) L-BFGS solver for linear regression does not accept general numeric label column types
Date Wed, 05 Oct 2016 23:19:20 GMT

     [ https://issues.apache.org/jira/browse/SPARK-17792?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-17792:
------------------------------------

    Assignee: Apache Spark

> L-BFGS solver for linear regression does not accept general numeric label column types
> --------------------------------------------------------------------------------------
>
>                 Key: SPARK-17792
>                 URL: https://issues.apache.org/jira/browse/SPARK-17792
>             Project: Spark
>          Issue Type: Bug
>          Components: ML
>            Reporter: Seth Hendrickson
>            Assignee: Apache Spark
>            Priority: Minor
>
> There's a bug in accepting numeric types for linear regression. We cast the label to
{{DoubleType}} in one spot where we use normal solver, but not for the l-bfgs solver. The
following can reproduce the problem:
> {code}
> import org.apache.spark.ml.feature.LabeledPoint
> import org.apache.spark.ml.linalg.{Vector, DenseVector, Vectors}
> import org.apache.spark.ml.regression.LinearRegression
> import org.apache.spark.sql.types._
> val df = Seq(LabeledPoint(1.0, Vectors.dense(1.0))).toDF().withColumn("weight", lit(1.0).cast(LongType))
> val lr = new LinearRegression().setSolver("l-bfgs").setWeightCol("weight")
> lr.fit(df)
> {code}



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