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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 Tue, 19 May 2015 13:24:59 GMT

    [ https://issues.apache.org/jira/browse/FLINK-1745?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14550425#comment-14550425
] 

ASF GitHub Bot commented on FLINK-1745:
---------------------------------------

GitHub user chiwanpark opened a pull request:

    https://github.com/apache/flink/pull/696

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

    This PR is not final but work in progress. You can see detail description in [JIRA](https://issues.apache.org/jira/browse/FLINK-1745).

You can merge this pull request into a Git repository by running:

    $ git pull https://github.com/chiwanpark/flink FLINK-1745

Alternatively you can review and apply these changes as the patch at:

    https://github.com/apache/flink/pull/696.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

    This closes #696
    
----
commit 804abe12c9503265171291a2841332341fe972be
Author: Chiwan Park <chiwanpark@icloud.com>
Date:   2015-05-15T05:45:50Z

    kNN join first draft

----


> 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: Chiwan Park
>              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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