On Thu, Aug 16, 2012 at 12:05 AM, Andrei Arsene Simion <[email protected]> wrote: > Hi, > > If I do a standard svm regression with e1071 > > x <- seq(0.1, 5, by = 0.05) > y <- log(x) + rnorm(x, sd = 0.2) > m <- svm(x, y) > > we can do predict(m,x) to get the fitted values. But what if I wan tho get > them by hand? > > Seem to me like it should be > > w = t(m$coefs)%*%m$SV > x.scaled = scale(x, m$x.scale[[1]], m$x.scale[[2]]) > t(w %*% t(as.matrix(x.scaled))) - m$rho but this is wrong > > If i get this right what the answer should be is > > f(x) = w%*%phi(x)+b but the question is what exactly is phi (by default) and > how do you do this if you cannot get phi in > closer form (rbf kernel?). It seems like the answer would lie with the dual > representation of the above, i think it is > > f(x) = sum_{support vectors}{(a_i-a*^{*}_{i})K(x_{i},x)}+b but how do you get > the a variables everything else. An actual formula would be greatly > appreciated!
I'll do you one better: getAnywhere(predict.svm) Though you might need to follow that down into the C code. Look into the /src/ directory of the package sources (not a binary) available from CRAN: http://cran.r-project.org/package=e1071 Huzzah for Open Source! Cheers, Michael > > Thanks! > > -Andrei > [[alternative HTML version deleted]] > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
