[jira] [Assigned] (SPARK-13028) Add MaxAbsScaler to ML.feature as a transformer

["Apache Spark (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-13028?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-13028:
------------------------------------

    Assignee:     (was: Apache Spark)

> Add MaxAbsScaler to ML.feature as a transformer
> -----------------------------------------------
>
>                 Key: SPARK-13028
>                 URL: https://issues.apache.org/jira/browse/SPARK-13028
>             Project: Spark
>          Issue Type: New Feature
>          Components: ML
>            Reporter: yuhao yang
>            Priority: Minor
>
> MaxAbsScaler works in a very similar way as MinMaxScaler, but scales in a way that the training data lies within the range [-1, 1] by dividing through the largest maximum value in each feature. The motivation to use this scaling include robustness to very small standard deviations of features and preserving zero entries in sparse data.
> Unlike StandardScaler and MinMaxScaler, MaxAbsScaler does not shift/center the data, and thus does not destroy any sparsity.
> Something similar from sklearn:
> http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MaxAbsScaler.html#sklearn.preprocessing.MaxAbsScaler



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