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https://issues.apache.org/jira/browse/FLINK-1745?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15031034#comment-15031034
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ASF GitHub Bot commented on FLINK-1745:
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Github user chiwanpark commented on the pull request:
https://github.com/apache/flink/pull/1220#issuecomment-160427679
Hi @danielblazevski, I reviewed your updated pull request. There are only
few problems to merge. Maybe after addressing them, we can merge this to master.
First, there are still some codes with style inconsistency. Could you
reformat all changes with your IDE? If you are using IntelliJ IDEA, you can do
reformatting by pressing Cmd+Alt+Shift+L or Ctrl+Alt+Shift+L.
About test case for `QuadTree`, adding a case to test `QuadTree` with
non-supported distance metric would be good. And I think splitting test case is
necessary. Many test run in a test case currently.
Some implementation doesn't seem scalaesque. I suggest more scalaesque
implementation. Could you review my suggestion?
> Add exact k-nearest-neighbours algorithm to machine learning library
> --------------------------------------------------------------------
>
> Key: FLINK-1745
> URL: https://issues.apache.org/jira/browse/FLINK-1745
> Project: Flink
> Issue Type: New Feature
> Components: Machine Learning Library
> Reporter: Till Rohrmann
> Assignee: Daniel Blazevski
> Labels: ML, Starter
>
> 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]
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