[ml] this week: fun with R?

[Ben Weisburd]

Hi Mike,
I'm looking for some help with these topics, so if somebody would be willing
to talk about them it would be much appreciated:
- feature selection for binary classification (or any classification) - when
you're just starting to work on a problem and have some ideas about possible
features, how do you decide which features are worth including? Lets say you
don't care about computational cost - should you just include all the
features you can think of? Or can some features actually hurt classification
performance (lets you're using SVMs)?
- iteratively improving performance - lets say you've picked a training set
of positive and negative examples, optimized meta-parameters through cross
validation, trained your classifier and run it to get some predictions. When
you look at the predictions, you see some that you think should have been
predicted the other way (based on your intuitive understanding of the data).
What should do?

-Ben




On Mon, Apr 25, 2011 at 2:49 PM, Mike Schachter <mike at mindmech.com> wrote:

> Does anyone want to present something this week or have
> a specific thing they'd like to talk about? If not, how about
> we just meet up and mess around with R? I'd like to get
> random forests going with some example code:
>
> http://cran.r-project.org/web/packages/randomForest/index.html
>
>  mike
> _______________________________________________
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> ml at lists.noisebridge.net
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>
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