[Pkg-exppsy-maintainers] New LARS classifier in PyMVPA!!!

[Greg Detre]

this looks awesome. dave blei independently mentioned LARS, since i 
think it'll sort out the choice of the lambda penalty parameter too

one point to note for your users - last time i tried to install RPy 
under ubuntu, the package was broken.

https://bugs.launchpad.net/ubuntu/+source/rpy/+bug/128180

i screwed about with it for a while, and the suggested fixes did help, 
but then i found that it crashed when i tried to plot stuff...

worth noting, even if you guys use debian

g


Per B. Sederberg wrote:
> Hi Folks:
>
> So I was talking with a world-famous mathematician (Ingrid Daubechies)
> about SMLR on Friday and she suggested trying out the Least Angle
> Regression (LARS) technique instead.  Here's the relevant paper by
> some of the most famous folks in machine learning:
>
> Bradley Efron, Trevor Hastie, Iain Johnstone and Robert Tibshirani,
> Least Angle Regression Annals of Statistics (with discussion) (2004)
> 32(2), 407-499. A new method for variable subset selection, with the
> lasso and "epsilon" forward stagewise methods as special cases.
>
> It is kind of like a smart boosted linear regression classifer where
> it adds features in one-by-one in a very intelligent fashion (those
> folks are smart.)
>
> She warned that implementing it may be a bit difficult due to a few
> tricks and suggested that I use some existing implementation from a
> person we can trust.  Well, it turns out that Trevor Hastie
> implemented it very nicely in R, so I figured let's make use of that
> PyMVPA framework and wrap it up!!!
>
> The result is a new LARS classifier that makes use of RPy to wrap the
> R implementation.  It looks like it works great and we should
> eventually make a LARSWeights to go with the SMLRWeights and
> LinearSVMWeights.
>
> To make it work, you have to install R and RPy and then download the
> lars contributed package.  Below are my notes on doing this on Debian:
>
> Howto install and use the R version of lars (on Debian Lenny):
>  - First you have to install all the R you need:
> <example>
> sudo aptitude install python-rpy python-rpy-doc r-base-dev
> </example>
>  - Then you have to install the lars library (if you do this as root
>    you will install it globally):
> <example>
> R
> install.package()
> </example>
>    Just pick your mirror, then pick lars from the list of packages.
>  - Finally this is how to use it with rpy:
> <example>
> ipython -pylab
> import rpy
> import numpy as N
> rpy.r.library('lars')
> x = N.random.randn(100,1000)
> x[:50,:5] = x[:50,:5] + 2
> x2 = N.random.randn(10,1000)
> x2[:5,:5] = x2[:5,:5] + 2
> y = N.zeros((100,1))
> y[:50,0] = 1
> res = rpy.r.lars(x,y,use_Gram=False)
> p = rpy.r.predict_lars(res,x2)
> </example>
>
>
> The current implementation passes the test_lars.py tests, but I was
> having a shogun error, so all the tests we not running on my machine.
>
> We should think about a graceful way for the code to error out if
> someone does not have the dependencies loaded correctly.
>
> Talk to ya'll soon,
> Per
>
> _______________________________________________
> Pkg-exppsy-maintainers mailing list
> Pkg-exppsy-maintainers at lists.alioth.debian.org
> http://lists.alioth.debian.org/mailman/listinfo/pkg-exppsy-maintainers
>   


-- 


---
Greg Detre
cell: 617 642 3902
email: greg at gregdetre.co.uk
web: http://www.princeton.edu/~gdetre/