[ml] decision trees / random forests?

[Glenn Wright]

Hey all, anyone have any background with decision trees, especially (what I
think are known as) ensemble methods such as random forests?  Straight out
of the Stanford class I found an interesting problem to work on, but for a
variety of reasons I think it might work better with decision trees than
with neural networks.  Unfortunately, that's not an area we covered in the
class.

I programmed a very simple, non-ensemble implementation by hand, and while
it's ridiculously slow, it does seem to solve the problem.  So I downloaded
the "milk" python library, which uses NumPy, and tried running its
(obviously much faster) random forest model.  And...well...it seems to be
getting the right answers, but I'm getting to the point where I'd like to
compare notes with someone before I get too far out on a limb.  Get it?
Out on a limb?  Trees?  Okay, I'll shut up now :)

-- 
-Glenn
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