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From "Richard Tomsett (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAHOUT-59) Create some examples of clustering well-known datasets
Date Thu, 19 Feb 2009 12:34:02 GMT

    [ https://issues.apache.org/jira/browse/MAHOUT-59?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12674983#action_12674983
] 

Richard Tomsett commented on MAHOUT-59:
---------------------------------------

Re: discussion of text clustering on the mailing list, there are several 'bag of words' examples
at the UCI repository: http://archive.ics.uci.edu/ml/datasets/Bag+of+Words . The data is in
[docID wordID wordcount] format so needs to be processed into TF-IDF Vectors for clustering.
I previously did this with a Python script but I'll write something in Hadoop to do it, before
passing it on to Canopy or K-Means clustering. May take a little while as I haven't looked
at my code for about half a year, and I didn't write unit tests or anything last time...

This would also involve writing a cosine distance measure class, which I guess would be useful
generally. Would this be a useful example?

> Create some examples of clustering well-known datasets
> ------------------------------------------------------
>
>                 Key: MAHOUT-59
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-59
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Clustering
>            Reporter: Jeff Eastman
>         Attachments: MAHOUT-59.patch
>
>
> The existing unit tests for clustering need to be augmented with examples from the literature
which illustrate its correct operation on datasets which have known clusters present. See
http://archive.ics.uci.edu/ml/ for some candidate datasets.

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