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https://issues.apache.org/jira/browse/SPARK-13028?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15118561#comment-15118561
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Apache Spark commented on SPARK-13028:
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User 'hhbyyh' has created a pull request for this issue:
https://github.com/apache/spark/pull/10939
> 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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