[R] Classifying Intertwined Spirals

[Joshua Gilbert]

When armed with barely enough information to be dangerous you would be
amazed at what I am willing to believe.

Thank you for pointing out how foolish I was.


Josh.


On 1/27/06, Liaw, Andy <andy_liaw at merck.com> wrote:
> You don't really expect SVM to give you good performance with no parameter
> tuning at all, do you?
>
> Try:
>
> m2 <- best.svm(class~., data=spiral, gamma=2^(-3:3), cost=2^(0:5))
> plot(m2, spiral)
>
> Andy
>
> From: Joshua Gilbert
> >
> > I'm using an SVM as I've seen a paper that reported extremely good
> > results. I'm not having such luck. I'm also interested in ideas for
> > other approaches to the problem that can also be applied to general
> > problems (no assuming that we're looking for spirals).
> >
> > Here is my code:
> > library(mlbench)
> > library(e1071)
> > raw <- mlbench.spirals(194, 2)
> > spiral <- data.frame(class=as.factor(raw$classes),
> > xx=raw$x[,1], y=raw$x[,2])
> > m <- svm(class~., data=spiral)
> > plot(m, spiral)
> >
> > You'll note that I have two spirals with 97 points each and I'm using
> > a kernel with a radial basis: exp(-gamma*|u-v|^2).
> >
> > You should be able to see a PNG of the resulting plot here:
> > http://www.flickr.com/photos/60118409@N00/91835679/
> >
> > The problem is that that's not good enough. I want a better fit. I
> > think I can get one, I just don't know how.
> >
> > There's a paper on Proximal SVMs that claims a better result. To the
> > best of my knowledge, PSVMs should not outperform SVMs, they are
> > merely faster to compute. You can find the paper (with the picture of
> > their SVM) on citeseer:
> > http://citeseer.ifi.unizh.ch/cachedpage/515368/5
> > @misc{ fung-proximal,
> >   author = "G. Fung and O. Mangasarian",
> >   title = "Proximal support vector machine classifiers",
> >   text = "G. Fung and O. Mangasarian. Proximal support vector machine
> > classifiers.
> >     In F. P. D. Lee and R. Srikant, editors, KDD",
> >   url = "citeseer.ifi.unizh.ch/515368.html" }
> >
> > I don't have much of a background in SVMs, I'm learning as I go, so
> > please don't hold back 'simple-minded' suggestions.
> >
> > I'm also asking the authors, but I'm not expecting a reply from them.
> >
> > There was a paper by Lang and Whitbrock in 1988 (Learning to Tell Two
> > Spirals Apart) that solved the problem with a neural network, but they
> > used a very specialized network architecture. I would say that
> > discovering such an architecture and then optimizing it would be very
> > time-intensive.
> >
> > Thank you for any response.
> >
> > Josh.
> >
> > ______________________________________________
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> > http://www.R-project.org/posting-guide.html
> >
> >
>
>
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