[ml] This week: KDD, next week: Hadoop!

Mike Schachter mike at mindmech.com
Mon May 17 21:31:46 PDT 2010


Hey everyone!

Just got back the other day and looking forward to meeting up Wednesday
and hearing about Hadoop. I just read a bit through the KDD challenge, and
was wondering if I could help out by doing something involving neural nets?

Neural nets can be made good at generalization and prediction, and also
reducing problem dimensionality by clustering. For example, we could
cluster the input records into groups, and pass that group data into an SVM
or something. Or we could use some sort of dimensionality reducing network
and pass the dimensionally-reduced dataset to a bayesian learner (which
wouldn't work well if the data was high dimensional).

If someone was already thinking of doing this I'd be happy to help out,
can't
glean much of what happened from the meeting notes.

See you Wednesday!

  mike



On Wed, May 12, 2010 at 10:05 PM, Thomas Lotze <thomas.lotze at gmail.com>wrote:

> Hello, all!  There was a good meeting today where we talked about the KDD
> dataset and plans for the next steps.  I think it'll be a really good
> opportunity for learning new tools and methods on machine learning, trading
> knowledge and upping our collective ability!  We've got plans to look at R,
> libsvm, weka, and Hadoop to tackle the problem.  I'm excited about working
> with it, and anyone else who wants to get involved should email me, download
> the data, and take a look at the wiki page I've put our initial plans in:
>
> https://www.noisebridge.net/wiki/KDD_Competition_2010
>
>
> Next week, Vikarem will be presenting Hadoop, with some scripts and tools
> to actually use it -- I think we're all aware of how important Hadoop
> already is and will continue to be in the future for analyzing large data
> sets, so I'm really glad that we've now got someone who knows about it and
> is willing to tell us more!  I think this is a really great opportunity, and
> many thanks to Vikarem for presenting!
>
>
> Best wishes,
> Thomas
>
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