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https://issues.apache.org/jira/browse/MAHOUT-843?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13166788#comment-13166788
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Paritosh Ranjan commented on MAHOUT-843:
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Ah, Its a mistake. I meant to write MeanShiftClustering, which is actually a
bottom up clustering. But yes, it can also be used, so, leaving the choice of
clustering algorithm to the user would be the best thing. I will update the
wiki.
Since I have not used CLI yet, I will have to learn how to use it and then I
will update the wiki. It might take few days. But I will update it for sure.
Few questions,
Is there any need to work on the Java API for top down clustering as I proposed
earlier ( with ClusterConfigs and ClusterExecutors )? I don't see much use of
that now. As the user can pretty easily do top-middle-middle-...-middle-bottom
clustering. I hope you will agree too.
Secondly, what other things are in "to be implemented" bucket of Clustering. I
have some time in hand and I would like to contribute more to Mahout. So, it
would be really helpful if you can guide me towards other things that needs to
be done. I won't mind looking into a new thing also which might involve some
reading/analysis/homework.
> Top Down Clustering
> -------------------
>
> Key: MAHOUT-843
> URL: https://issues.apache.org/jira/browse/MAHOUT-843
> Project: Mahout
> Issue Type: New Feature
> Components: Clustering
> Affects Versions: 0.6
> Reporter: Paritosh Ranjan
> Assignee: Jeff Eastman
> Labels: clustering, patch
> Fix For: 0.6
>
> Attachments: MAHOUT-843-patch, MAHOUT-843-patch-only-postprocessor,
> MAHOUT-843-patch-only-postprocessor-final,
> MAHOUT-843-patch-only-postprocessor-v1,
> MAHOUT-843-patch-only-postprocessor-v2,
> MAHOUT-843-patch-only-postprocessor-v3,
> MAHOUT-843-patch-only-postprocessor-v4,
> MAHOUT-843-patch-only-postprocessor-v5, MAHOUT-843-patch-v1,
> Top-Down-Clustering-patch
>
>
> Top Down Clustering works in multiple steps. The first step is to find
> comparative bigger clusters. The second step is to cluster the bigger chunks
> into meaningful clusters. This can performance while clustering big amount of
> data. And, it also removes the dependency of providing input clusters/numbers
> to the clustering algorithm.
> The "big" is a relative term, as well as the smaller "meaningful" terms. So,
> the control of this "bigger" and "smaller/meaningful" clusters will be
> controlled by the user.
> Which clustering algorithm to be used in the top level and which to use in
> the bottom level can also be selected by the user. Initially, it can be done
> for only one/few clustering algorithms, and later, option can be provided to
> use all the algorithms ( which suits the case ).
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