Carsten Schnober created SPARK-10356:
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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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