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From Matias Bjørling (JIRA) <j...@apache.org>
Subject [jira] Updated: (MAHOUT-173) Implement clustering of massive-domain attributes
Date Sun, 06 Sep 2009 08:46:57 GMT

     [ https://issues.apache.org/jira/browse/MAHOUT-173?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Matias Bjørling updated MAHOUT-173:
-----------------------------------

    Remaining Estimate: 30h  (was: 2016h)
     Original Estimate: 30h  (was: 2016h)

Changing estimate. It will be done in three months, but estimate is only 30 hours.

> Implement clustering of massive-domain attributes
> -------------------------------------------------
>
>                 Key: MAHOUT-173
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-173
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Clustering
>            Reporter: Matias Bjørling
>            Priority: Trivial
>   Original Estimate: 30h
>  Remaining Estimate: 30h
>
> Implement the Clustering algorithm described in "A Framework for Clustering Massive-Domain
Data Streams" by Chary C. Aggarwal.
> Steps: 
> 1. Implement baseline solution to compare solutions.
> 2. Figure out how to implement the loading of clustering by looking at the k-means implementation.
> 3. Implement Count-Min sketch algorithm for each cluster.
> 4. Find out how to give the user the power to choose the distance function for the input
data ( Maybe already possible? )

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