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 <[EMAIL PROTECTED]> 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/[EMAIL PROTECTED]/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. > > > > ______________________________________________ > > R-help@stat.math.ethz.ch mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide! > > http://www.R-project.org/posting-guide.html > > > > > > > ------------------------------------------------------------------------------ > Notice: This e-mail message, together with any attachment...{{dropped}} ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html