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Date: Wed, 23 Mar 2016 17:53:25 +0000 (UTC)
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Subject: [jira] [Commented] (FLINK-1745) Add exact k-nearest-neighbours
 algorithm to machine learning library
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    [ https://issues.apache.org/jira/browse/FLINK-1745?page=3Dcom.atlassian=
.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=3D1520=
8861#comment-15208861 ]=20

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

Github user tillrohrmann commented on the pull request:

    https://github.com/apache/flink/pull/1220#issuecomment-200465211
 =20
    Hi Daniel, the docs are handwritten as far as I know.
   =20
    On Wed, Mar 23, 2016 at 5:49 PM, Daniel Blazevski <notifications@github=
.com>
    wrote:
   =20
    > @chiwanpark <https://github.com/chiwanpark> about the docs, when I lo=
ok
    > at docs/libs/ml/smv.md for instance (or als.md, etc.), the parameters
    > section seems auto-generated, is that correct? Is so, do you know how=
 this
    > was auto-generated? If not, I'll use the existing docs as a template.
    >
    > =E2=80=94
    > You are receiving this because you were mentioned.
    > Reply to this email directly or view it on GitHub
    > <https://github.com/apache/flink/pull/1220#issuecomment-200436234>
    >


> 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 trivi=
al it is still used as a mean to classify data and to do regression. This i=
ssue focuses on the implementation of an exact kNN (H-BNLJ, H-BRJ) algorith=
m 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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