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https://issues.apache.org/jira/browse/FLINK-1745?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15289259#comment-15289259
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ASF GitHub Bot commented on FLINK-1745:
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Github user tillrohrmann commented on the pull request:
https://github.com/apache/flink/pull/1220#issuecomment-220083900
The PR looks good to me. The only think which could be good to get rid of
is the requirement that you have to select a Euclidean distance for the
quadtree. Maybe there is some other characteristic for a distance measure which
says whether it's applicable for quadtrees or not. Then we could introduce a
new distance metric type to make sure that only appropriate distance measures
are used. But this should not be a blocker for merging this PR.
Thanks for your contribution @danielblazevski. Really good work :-)
> 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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