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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-1745) Add exact k-nearest-neighbours algorithm to machine learning library
Date Fri, 14 Aug 2015 12:01:45 GMT

    [ https://issues.apache.org/jira/browse/FLINK-1745?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14696929#comment-14696929

ASF GitHub Bot commented on FLINK-1745:

Github user chiwanpark commented on the pull request:

    @kno10 Thanks for the comment. In this case we don't need to parallelize R-Tree because
R-Tree is only used in reducer for matching records of the given block pair.
    But I agree that exact k-NN implementation doesn't fit large-scale data. We can discuss
in other [JIRA issue](https://issues.apache.org/jira/browse/FLINK-1934).
    I'm inclined to close this PR and FLINK-1745 because many people says exact k-NN is not
good and I think so. May I close them? @thvasilo @tillrohrmann 

> 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
>              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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