[SPARK-7535] Audit Pipeline APIs for 1.4

• Type: Sub-task
• Status: Resolved
• Priority: Major
• Resolution: Fixed
• Fix Version/s: 1.4.0
• Component/s: ML, PySpark
• Target Version/s: 1.4.0
• Assignee: Xiangrui Meng
• Reporter: Joseph K. Bradley
• Created: 11/May/15 19:24
• Updated: 27/May/15 06:52
• Resolved: 27/May/15 06:51

Description

This is an umbrella for auditing the Pipeline (spark.ml) APIs. Items to check:

• Public/protected/private access
• Consistency across spark.ml
• Classes, methods, and parameters in spark.mllib but missing in spark.ml
  • We should create JIRAs for each of these (under an umbrella) as to-do items for future releases.

For each algorithm or API component, create a subtask under this umbrella. Some major new items:

• new feature transformers
• tree models
• elastic-net
• ML attributes
• developer APIs (Predictor, Classifier, Regressor)

Issue Links

• contains: SPARK-7740 Improve Evaluator doc to state that higher metric values are better.
• links to: [Github] Pull Request #6322 (mengxr)
• links to: [Github] Pull Request #6392 (mengxr)