Saikat,
I have created https://issues.apache.org/jira/browse/MAHOUT-981 for
refactoring KMeansDriver to use the new ClusterClassificationDriver.
You can provide your patches on this issue. See this to know how to
provide a patch
https://cwiki.apache.org/MAHOUT/how-to-contribute.html#HowToContribute-Generatingapatch.
Before KMeans refactoring, we are expecting the
ClusterClassificationMapperTest from you ( for Mahout-929 ). That test
case would complete the development of ClusterClassificationDriver and
the refactoring can start.
Paritosh
On 23-02-2012 04:55, Jeff Eastman wrote:
Hi Saikat,
Glad you're excited. Paritosh offered one suggestion below. You could
look at TestKmeansClustering for patterns you could use to test the
ClusterClassificationMapper and Driver in MR mode. That should be
straightforward, but please coordinate with Paritosh so you don't
duplicate efforts.
Another place you might look into would be the KMeansDriver and
MAHOUT-930. You could work on refactoring KMeansDriver to use the new
ClusterClassificationDriver in MAHOUT-929. That would exercise both
its sequential and MR options. It will be interesting to see how much
code can be removed.
Finally, you could see if you can wrap your mind around the
ClusterIterator and how it could be used for further refactoring of
the KMeansDriver. See TestClusterClassifier for insight.
That enough reading and doing for now?
Jeff
On 2/22/12 10:06 AM, Saikat Kanjilal wrote:
Jeff,I'm pretty excited to help out with this, so as a starter can
you point me to where I should begin my readings of the code, I
havent looked too closely but are there certain classes in the
clustering area where this refactoring effort is centered around.
Regards
Date: Wed, 22 Feb 2012 08:56:23 -0700
From: [email protected]
To: [email protected]
Subject: Re: Helping out with the .7 release
Hi Saikat,
I agree with Paritosh, that a great place to begin would be to write
some unit tests. This will familiarize you with the code base and help
us a lot with our 0.7 housekeeping release. The new clustering
classification components are going to unify many - but not all - of
the
existing clustering algorithms to reduce their complexity by factoring
out duplication and streamlining their integration into semi-supervised
classification engines.
Please feel free to post any questions you may have in reading through
this code. This is a major refactoring effort and we will need all the
help we can get. Thanks for the offer,
Jeff
On 2/21/12 10:46 PM, Saikat Kanjilal wrote:
Hi Paritosh,Yes creating the test case would be a great first
start, however are there other tasks you guys need help with before
I can do before the test creation, I will sync trunk and start
reading through the code in the meantime.Regards
Date: Wed, 22 Feb 2012 10:57:51 +0530
From: [email protected]
To: [email protected]
Subject: Re: Helping out with the .7 release
We are creating clustering as classification components which will
help
in moving clustering out. Once the component is ready, then the
clustering algorithms would need refactoring.
The clustering as classification component and the outlier removal
component has been created.
Most of it is committed, and rest is available as a patch. See
https://issues.apache.org/jira/browse/MAHOUT-929
If you will apply the latest patch available on Mahout-929 you can
see
all that is available now.
If you want, you can help with the test case of
ClusterClassificationMapper available in the patch.
On 22-02-2012 10:27, Saikat Kanjilal wrote:
Hi Guys,I was interested in helping out with the clustering
component of mahout, I looked through the JIRA items below and
was wondering if there is a specific one that would be good to
start with:
https://issues.apache.org/jira/secure/IssueNavigator.jspa?reset=true&jqlQuery=project+%3D+MAHOUT+AND+resolution+%3D+Unresolved+AND+component+%3D+Clustering+ORDER+BY+priority+DESC&mode=hide
I initially was thinking to work on Mahout-930 or Mahout-931 but
could work on others if needed.
Best Regards
