[SPARK-2336] Approximate k-NN Models for MLLib

• Type: New Feature
• Status: Resolved
• Priority: Minor
• Resolution: Won't Fix
• Component/s: MLlib
• Labels: clustering features
• Assignee: Unassigned
• Reporter: Brian Gawalt
• Created: 01/Jul/14 18:26
• Updated: 24/Feb/17 18:25
• Resolved: 24/Feb/17 18:25

Description

After tackling the general k-Nearest Neighbor model as per https://issues.apache.org/jira/browse/SPARK-2335 , there's an opportunity to also offer approximate k-Nearest Neighbor. A promising approach would involve building a kd-tree variant within from each partition, a la

http://www.autonlab.org/autonweb/14714.html?branch=1&language=2

This could offer a simple non-linear ML model that can label new data with much lower latency than the plain-vanilla kNN versions.

Issue Links

• depends upon: SPARK-2335 k-Nearest Neighbor classification and regression for MLLib
• is duplicated by: SPARK-2335 k-Nearest Neighbor classification and regression for MLLib