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https://issues.apache.org/jira/browse/MAHOUT-1177?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13665203#comment-13665203
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Shannon Quinn commented on MAHOUT-1177:
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Yu Lee and Yexi: For the time being, I'd be on board with shelving the addition
of any new clustering algorithms, and instead focusing on improving
documentation and unifying the APIs for the existing ones. I think that would
help scope your work a little more effectively, while still providing an
extremely valuable body of work. Plus, it would greatly aid the development of
new algorithms to have a specific interface to build into. Beyond that, I think
your ideas are good and would encourage you to start laying out your specific
plans.
Ravi: I would suggest browsing the open JIRAs for Mahout and to submit a patch
for one you think you can tackle. Please feel free to ping our email list if
you have specific questions, though for general ones please submit them to the
list rather than on JIRA.
> GSOC 2013: Reform and simplify the clustering APIs
> --------------------------------------------------
>
> Key: MAHOUT-1177
> URL: https://issues.apache.org/jira/browse/MAHOUT-1177
> Project: Mahout
> Issue Type: Improvement
> Reporter: Dan Filimon
> Labels: gsoc2013, mentor
>
> Clustering is one of the most used features in Mahout and has many
> applications [http://en.wikipedia.org/wiki/Cluster_analysis#Applications].
> We have of lots clustering algorithms. There's:
> - basic k-means
> - canopy clustering
> - Dirichlet clustering
> - Fuzzy k-means
> - Spectral k-means
> - Streaming k-means [coming soon]
> We want to make them easier to use by updating the APIs and make sure they
> all work in the same way have consistent inputs, outputs, diagnostics and
> documentation.
> This is a great way to gain an in-depth understanding of clustering
> algorithms, familiarize yourself with Hadoop, Mahout clustering and good
> software engineering principles.
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