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https://issues.apache.org/jira/browse/SPARK-17934?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15707710#comment-15707710
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yuhao yang commented on SPARK-17934:
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We can probably implement something like Robust Scaler in sklearn.
http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.RobustScaler.html
> Support percentile scale in ml.feature
> --------------------------------------
>
> Key: SPARK-17934
> URL: https://issues.apache.org/jira/browse/SPARK-17934
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Reporter: Lei Wang
>
> Percentile scale is often used in feature scale.
> In my project, I need to use this scaler.
> Compared to MinMaxScaler, PercentileScaler will not produce unstable result
> due to anomaly large value.
> About percentile scale, refer to https://en.wikipedia.org/wiki/Percentile_rank
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