[jira] [Commented] (MATH-1031) Refactoring: Move variance calculation of a centroid cluster to its class

["Thomas Neidhart (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/MATH-1031?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13817399#comment-13817399 ] 

Thomas Neidhart commented on MATH-1031:
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Yes indeed, I plan to commit this change soon.

btw. there is also MATH-959 to add a hierarchical clusterer to CM.
I have already added a preliminary patch which contains an optimial algorithm for single-link.

The remaining link-methods are still to be implemented or will be implemented with a naive algorithm which is straight-forwards.

In case you have some interest in this.

> Refactoring: Move variance calculation of a centroid cluster to its class
> -------------------------------------------------------------------------
>
>                 Key: MATH-1031
>                 URL: https://issues.apache.org/jira/browse/MATH-1031
>             Project: Commons Math
>          Issue Type: Improvement
>    Affects Versions: 3.2
>            Reporter: Thorsten Schäfer
>            Priority: Minor
>         Attachments: centroid.patch
>
>
> Users might be interested in assessing the quality of each cluster in the calculated clustering. This can be performed by calculating its variance. 
> The variance calculation is actually performed in other places (e.g. for the MultiKMeans), but not available to end users. 
> I'd propose to add the functionality into the CentroidCluster. The one issue to consider is that the cluster does not know based on which distance measure it was calculated. In the implementation, I chose to parametrize the method with a distance measure which enables users to also compare the quality based on various distance measures. Alternatively, it would be possible to add the distance measure as a field, which is set by the clustering algorithm.
> In the patch I went for the first method and also changed the 2 other places where variance calculation is performed to use the new feature.



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