flink-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-1745) Add exact k-nearest-neighbours algorithm to machine learning library
Date Wed, 14 Oct 2015 15:38:05 GMT

    [ https://issues.apache.org/jira/browse/FLINK-1745?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14957094#comment-14957094
] 

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

Github user danielblazevski commented on the pull request:

    https://github.com/apache/flink/pull/1220#issuecomment-148088594
  
    Thanks @tillrohrmann, I changed my code using the .asBreeze and .fromBreeze.  I think
I am now having trouble linking to the Breeze library.  When I now try to construct the QuadTree,
I get the error (by printing "hello" to the console, I checked and KNN.scala runs up until
the calling of the QuadTree constructor, which now has an import statement `import Breeze._`
and KNN.scala does not have that import statment ):
    
    Oct 14, 2015 11:26:51 AM com.github.fommil.netlib.BLAS <clinit>
    WARNING: Failed to load implementation from: com.github.fommil.netlib.NativeSystemBLAS
    Oct 14, 2015 11:26:51 AM com.github.fommil.netlib.BLAS <clinit>
    WARNING: Failed to load implementation from: com.github.fommil.netlib.NativeRefBLAS
    
    Is there a recommended to link and grab/install Breeze within Flink automatically, or
does the user have to have it separately installed?
    
    I made a new commit.


> 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]



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

Mime
View raw message