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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-17086) QuantileDiscretizer throws InvalidArgumentException (parameter splits given invalid value) on valid data
Date Mon, 22 Aug 2016 08:04:20 GMT

     [ https://issues.apache.org/jira/browse/SPARK-17086?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-17086:
------------------------------------

    Assignee: Apache Spark

> QuantileDiscretizer throws InvalidArgumentException (parameter splits given invalid value)
on valid data
> --------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-17086
>                 URL: https://issues.apache.org/jira/browse/SPARK-17086
>             Project: Spark
>          Issue Type: Bug
>          Components: ML
>    Affects Versions: 2.1.0
>            Reporter: Barry Becker
>            Assignee: Apache Spark
>
> I discovered this bug when working with a build from the master branch (which I believe
is 2.1.0). This used to work fine when running spark 1.6.2.
> I have a dataframe with an "intData" column that has values like 
> {code}
> 1 3 2 1 1 2 3 2 2 2 1 3
> {code}
> I have a stage in my pipeline that uses the QuantileDiscretizer to produce equal weight
splits like this
> {code}
> new QuantileDiscretizer()
>         .setInputCol("intData")
>         .setOutputCol("intData_bin")
>         .setNumBuckets(10)
>         .fit(df)
> {code}
> But when that gets run it (incorrectly) throws this error:
> {code}
> parameter splits given invalid value [-Infinity, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, Infinity]
> {code}
> I don't think that there should be duplicate splits generated should there be?



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