yuhao yang created SPARK-13028:
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Summary: 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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