[SPARK-13028] Add MaxAbsScaler to ML.feature as a transformer

• Type: New Feature
• Status: Resolved
• Priority: Minor
• Resolution: Fixed
• Fix Version/s: 2.0.0
• Component/s: ML
• Target Version/s: 2.0.0
• Assignee: yuhao yang
• Reporter: yuhao yang
• Shepherd: Xiangrui Meng
• Created: 27/Jan/16 03:18
• Updated: 26/Feb/16 05:05
• Resolved: 26/Feb/16 05:04

Description

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

Issue Links

• is depended upon by: SPARK-13505 Python API for MaxAbsScaler
• links to: [Github] Pull Request #10939 (hhbyyh)