[jira] [Work logged] (MATH-1374) KMeansPlusPlusClusterer unable to converge having repeatable points in input dataset

["ASF GitHub Bot (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MATH-1374?focusedWorklogId=375466&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-375466 ]

ASF GitHub Bot logged work on MATH-1374:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 22/Jan/20 08:19
            Start Date: 22/Jan/20 08:19
    Worklog Time Spent: 10m 
      Work Description: C0rWin commented on pull request #37: [MATH-1374]:Aadd center as first point of the cluster while seeding.
URL: https://github.com/apache/commons-math/pull/37
 
 
   
 
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Issue Time Tracking
-------------------

            Worklog Id:     (was: 375466)
    Remaining Estimate: 0h
            Time Spent: 10m

> KMeansPlusPlusClusterer unable to converge having repeatable points in input dataset
> ------------------------------------------------------------------------------------
>
>                 Key: MATH-1374
>                 URL: https://issues.apache.org/jira/browse/MATH-1374
>             Project: Commons Math
>          Issue Type: Bug
>            Reporter: Artem Barger
>            Assignee: Artem Barger
>            Priority: Major
>             Fix For: 4.0
>
>         Attachments: MATH-1374.patch
>
>          Time Spent: 10m
>  Remaining Estimate: 0h
>
> If the input list size of {{Clusterable}} is greater than parameter {{k}} while has less unique points than {{k}}, the algorithm will fail to converge, tested w/ different EmptyClusterStrategy options, here is the example of default one: 
> {code}
>    @Test
>     public void testNumberOfRequestedClustersSameAsInputSize() {
>         final RandomVectorGenerator rng = new UncorrelatedRandomVectorGenerator(10,
>                 new GaussianRandomGenerator(RandomSource.create(RandomSource.MT)));
>         List<DoublePoint> points = new ArrayList<>();
>         for (int i = 0; i < 10; i++) {
>             final DoublePoint point = new DoublePoint(rng.nextVector());
>             for (int j = 0; j < 3; j++) {
>                 points.add(point);
>             }
>         }
>         final KMeansPlusPlusClusterer<DoublePoint> clusterer = new KMeansPlusPlusClusterer<>(12);
>         clusterer.cluster(points);
>     }
> {code}



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