[FLINK-1745] Add exact k-nearest-neighbours algorithm to machine learning library

• Type: New Feature
• Status: Closed
• Priority: Major
• Resolution: Implemented
• Fix Version/s: 1.1.0
• Component/s: Library / Machine Learning
• Labels: ML Starter
• Assignee: Daniel Blazevski
• Reporter: Till Rohrmann
• Created: 19/Mar/15 10:16
• Updated: 26/Jul/16 15:59
• Resolved: 30/May/16 11:16

Description

Even though the k-nearest-neighbours (kNN) [1,2] algorithm is quite trivial it is still used as a mean to classify data and to do regression. This issue focuses on the implementation of an exact kNN (H-BNLJ, H-BRJ) algorithm as proposed in [2].

Could be a starter task.

Resources:

[1] http://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm
[2] https://www.cs.utah.edu/~lifeifei/papers/mrknnj.pdf

Issue Links

• is related to: FLINK-1934 Add approximative k-nearest-neighbours (kNN) algorithm to machine learning library
• requires: FLINK-1933 Add distance measure interface and basic implementation to machine learning library
• links to: GitHub Pull Request #1220
• links to: GitHub Pull Request #2048
• links to: GitHub Pull Request #2050