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https://issues.apache.org/jira/browse/FLINK-1745?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14985506#comment-14985506
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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-153078409
Hi @danielblazevski, Thanks for updating your pull request. I'll review
this soon. From short review, I think that we have to split predict method into
two methods because lots of `if(useQuadTree)` statements are duplicated.
I suggest creating two methods into `PredicateDataSetOperation`. One is
finding kNN with quad-tree and the other is not. We can pass testing data set
and training data set to the methods and receive result of the methods. I mean
the logic in L191-L270 of `KNN.scala`.
> 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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