[SPARK-2768] Add product, user recommend method to MatrixFactorizationModel

• Type: Improvement
• Status: Resolved
• Priority: Minor
• Resolution: Fixed
• Affects Version/s: 1.0.1
• Fix Version/s: 1.1.0
• Component/s: MLlib
• Target Version/s: 1.1.0
• Assignee: Sean R. Owen
• Reporter: Sean R. Owen
• Created: 31/Jul/14 10:30
• Updated: 15/Jan/15 09:08
• Resolved: 01/Aug/14 14:33

Description

Right now, MatrixFactorizationModel can only predict a score for one or more (user,product) tuples. As a comment in the file notes, it would be more useful to expose a recommend method, that computes top N scoring products for a user (or vice versa – users for a product).

Issue Links

• links to: [Github] Pull Request #1687 (srowen)