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Date: Sat, 23 Mar 2013 17:51:15 +0000 (UTC)
From: "Phil Steitz (JIRA)" <jira@apache.org>
To: issues@commons.apache.org
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Subject: [jira] [Commented] (MATH-917) More distance measurements are needed
 in o.a.c.m.stat.clustering.
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    [ https://issues.apache.org/jira/browse/MATH-917?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13611780#comment-13611780 ] 

Phil Steitz commented on MATH-917:
----------------------------------

In general, I like this. It may be best to do this as a replacement in 4.0, though, instead of yet another new package, moved for convenience.  My opinion is that this belongs where it is - in .stat. I agree with the rationale for the changes though, especially the second bullet. I have a couple of small comments:
* I think I agree, but want to make sure there is no loss in the first bullet.  Doing this effectively turns a Clusterable into a vector.  I don't have immediate use cases where this will not be true; but the existing setup is a bit more general and more logical to me - the distance measure is a property of the space of objects that are being clustered. I get your point about it making it a bit easier to implement the interface; but I want to make sure it does not end up cutting out some applications.
* I am curious why you chose to make CentroidBasedCluster and ClusterCenter inner classes of KMeansPlusPlusClusterer.
* Don't forget the javadoc of the modified Cluster::Cluster() should omit reference to the centroid.
                
> More distance measurements are needed in o.a.c.m.stat.clustering.
> -----------------------------------------------------------------
>
>                 Key: MATH-917
>                 URL: https://issues.apache.org/jira/browse/MATH-917
>             Project: Commons Math
>          Issue Type: Improvement
>            Reporter: Reid Hochstedler
>             Fix For: 4.0
>
>         Attachments: clustering.zip
>
>
> Currently only Euclidean distance is used for distance measurement, it would be easy to quickly add Manhattan and Chebyshev distance among others.

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