[jira] [Resolved] (SPARK-10356) MLlib: Normalization should use absolute values

["Sean Owen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-10356?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen resolved SPARK-10356.
-------------------------------
    Resolution: Not A Problem

> MLlib: Normalization should use absolute values
> -----------------------------------------------
>
>                 Key: SPARK-10356
>                 URL: https://issues.apache.org/jira/browse/SPARK-10356
>             Project: Spark
>          Issue Type: Bug
>          Components: MLlib
>    Affects Versions: 1.4.1
>            Reporter: Carsten Schnober
>              Labels: easyfix
>   Original Estimate: 2h
>  Remaining Estimate: 2h
>
> The normalizer does not handle vectors with negative values properly. It can be tested with the following code
> {code}
> val normalized = new Normalizer(1.0).transform(v: Vector)
> normalizer.toArray.sum == 1.0
> {code}
> This yields true if all values in Vector v are positive, but false when v contains one or more negative values. This is because the values in v are taken immediately without applying {{abs()}},
> This (probably) does not occur for {{p=2.0}} because the values are squared and hence positive anyway.



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