[SPARK-15041] adding mode strategy for ml.feature.Imputer for categorical features

• Type: New Feature
• Status: Resolved
• Priority: Minor
• Resolution: Incomplete
• Component/s: ML
• Labels: bulk-closed
• Assignee: Unassigned
• Reporter: yuhao yang
• Created: 30/Apr/16 16:39
• Updated: 08/Oct/19 05:41
• Resolved: 08/Oct/19 05:41

Description

Adding mode strategy for ml.feature.Imputer for categorical features. This need to wait until PR for SPARK-13568 gets merged.
https://github.com/apache/spark/pull/11601

From comments of jkbradley and Nick Pentreath in the PR

Investigate efficiency of approaches using DataFrame/Dataset and/or approx approaches such as frequentItems or Count-Min Sketch (will require an update to CMS to return "heavy-hitters").
investigate if we can use metadata to only allow mode for categorical features (or perhaps as an easier alternative, allow mode for only Int/Long columns)

Issue Links

• is blocked by: SPARK-13568 Create feature transformer to impute missing values