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ASF GitHub Bot commented on FLINK-1731: --------------------------------------- GitHub user peedeeX21 opened a pull request: https://github.com/apache/flink/pull/700 [FLINK-1731] [ml] Implementation of Feature K-Means and Test Suite Within the IMPRO-3 warm-up task the implementation of K-Means and corresponding test suite was done. You can merge this pull request into a Git repository by running: $ git pull https://github.com/peedeeX21/flink feature_kmeans Alternatively you can review and apply these changes as the patch at: https://github.com/apache/flink/pull/700.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 #700 ---- commit 02fe6b2c7ebc6bf4b55e832681286994b03c4d40 Author: Florian Goessler <m...@floriangoessler.de> Date: 2015-05-20T09:12:20Z [FLINK-1731] [ml] unit test for KMeans commit 71aa47bd06ad2e051749ea1b9df923b8eb5bf6e4 Author: Peter Schrott <peter.schrot...@gmail.com> Date: 2015-05-20T11:08:36Z [FLINK-1731] [ml] Implementation of K-Means ---- > 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: Peter Schrott > 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 -- This message was sent by Atlassian JIRA (v6.3.4#6332)