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From "Paritosh Ranjan (Updated) (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (MAHOUT-843) Top Down Clustering
Date Fri, 11 Nov 2011 04:10:51 GMT

     [ https://issues.apache.org/jira/browse/MAHOUT-843?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Paritosh Ranjan updated MAHOUT-843:
-----------------------------------

    Attachment: MAHOUT-843-patch-only-postprocessor-v1

I have taken all incoming changes and created the patch. Also added TopDownClusteringPathConstants.
Can't see any other external reference.

The clusterDataMR and clusterDataSeq, both overwrite the clusteredPoints when the input file
provided has more than one paths, which is the case in the input of bottom level cluster.


The test case does top level clustering, asserts cluster output processor, both of which works
fine. Then it is asserting bottom level clustering which shows the problem. Only one point
is written(overridden) in one cluster. This can be seen while debugging clusterDataSeq.
                
> 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
>              Labels: clustering, patch
>             Fix For: 0.6
>
>         Attachments: MAHOUT-843-patch, MAHOUT-843-patch-only-postprocessor, MAHOUT-843-patch-only-postprocessor-v1,
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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