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Hi, this is a question about the R package kernlab. I use kernlab as a library in a C++ program. The host application defines a graph kernel (defined by me), generates a gram matrix and trains kernlab directly on this gram matrix, like this: regm<-ksvm(K,y,kernel="matrix"), where K is the n x n gram kernelMatrix of my kernel, and y is the R-vector of quantitative target values. So, to make sure you got it: I don't want kernlab to compute the kernel values by itself. Rather, this is a task for the host application. Learn...

...841 } 842 else 843 scal <- 1 844 error(ret) <- drop((scal^2)*crossprod(fitted(ret) - y)/m) 845 } 846 } C. Finally, an example (taken from ?ksvm): require (kernlab) seed (1234) x <- seq(-20,20,0.1); x <- x[x != 0] y <- sin(x)/x + rnorm(400,sd=0.03) regm <- ksvm(x,y,epsilon=0.01,kpar=list(sigma=16),cross=3) te <- crossprod (fitted(regm)-y)/400 s <- (scaling(regm)$y.scale[["scaled:scale"]])^2 error (regm) # 0.03891344 te # 0.0008958718 te * s # 6.37252e-05 te / s # 0.01259449 These numbers can also be s...