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

["Carsten Schnober (JIRA)" <ji...@apache.org>]

Carsten Schnober created SPARK-10356:
----------------------------------------

             Summary: 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


The normalizer does not handle vectors with negative values properly. It can be tested with the following code

{{
val normalized = new Normalizer(1.0).transform(v: Vector)
normalizer.toArray.sum == 1.0
}}

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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