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Date: Thu, 7 May 2015 14:22:59 +0000 (UTC)
From: "Till Rohrmann (JIRA)" <jira@apache.org>
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Subject: [jira] [Comment Edited] (FLINK-1731) Add kMeans clustering
 algorithm to machine learning library
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    [ https://issues.apache.org/jira/browse/FLINK-1731?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14532722#comment-14532722 ] 

Till Rohrmann edited comment on FLINK-1731 at 5/7/15 2:22 PM:
--------------------------------------------------------------

I just merged the PR with the distance metrics. You can use it now.

At the moment I think it's easier to simply use the {{BreezeVector}} if you want to do vector manipulations.


was (Author: till.rohrmann):
I just merged the PR with the distance metrics. You can use it now.

At the moment I think it's easier to simply use the {BreezeVector} if you want to do vector manipulations.

> Add kMeans clustering algorithm to machine learning library
> -----------------------------------------------------------
>
>                 Key: FLINK-1731
>                 URL: https://issues.apache.org/jira/browse/FLINK-1731
>             Project: Flink
>          Issue Type: New Feature
>          Components: Machine Learning Library
>            Reporter: Till Rohrmann
>            Assignee: Alexander Alexandrov
>              Labels: ML
>
> The Flink repository already contains a kMeans implementation but it is not yet ported to the machine learning library. I assume that only the used data types have to be adapted and then it can be more or less directly moved to flink-ml.
> The kMeans++ [1] and the kMeans|| [2] algorithm constitute a better implementation because the improve the initial seeding phase to achieve near optimal clustering. It might be worthwhile to implement kMeans||.
> Resources:
> [1] http://ilpubs.stanford.edu:8090/778/1/2006-13.pdf
> [2] http://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf


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