search for: kpca

Hi! The kernlab function kpca() mentions that new observations can be transformed by using predict. Theres also an example in the documentation, but as you can see i am getting an error there (As i do with my own data). I'm not sure whats wrong at the moment. I haven't any predict functions written by myself in the work...

Hi! how do i get to the source code of kpca or even better predict.kpca(which it tells me doesn't exist but should) ? (And if anyone has too much time: Now if i got that right, the @pcv attribute consists of the principal components, and for kpca, these are defined as projections of some random point x, which was transformed into the o...

...found a problem with the code of one of the libraries (not core), or, in my current case, would wish something minor changed for convenience, where can i get contact? Can i put it in the "official" bug repository? (Problem discription for anyone interested: Why call the default function kpca for a matrix with kpar=list(sigma=0.2), instead of putting this default sigma into the rbfkernel and using kpar=list()? Anytime i call kpca with a kernel without sigma, i have to supply kpar=list() or get an error. )

...o plot the results of my %PCA (via the function dudi.pca()) followed by a MCOA (mcoa()). But when I give my variables to s.multinom() I get the following Error message: Error in FUN(1:14[[1L]], ...) : number 1 profile without data I know that it has to do with one (or two?) of the first arguments (kpca,sglmarkerfrq) but I just don't get what this error means nor what I can do to fix it. I have successfully done all the same procedure with a set of raw data already, only difference of the data now is that I don't use the raw allelic frequencies as input for the %PCA but instead their natur...

Hi everybody, I''m using R on a 64-bit Ubuntu 9.04 (Jaunty). I prefer to install R packages from source, even if they are available in Synaptic. The problem is that I can''t install/compile kernlab. Everything works fine until it gets to the lazy loading part: ** preparing package for lazy loading Creating a new generic function for "terms" in "kernlab"

...o rvm() : Relevance Vector Machines for regression o specc() : Spectral Clustering o kkmeans() : Kernel k-means clustering o ranking() : Kernel-based ranking method o onlearn() : Kernel-based Online Learning algorithms for classification, novelty detection and regression o kpca() : Kernel Pricipal Components Analysis o kcca() : Kernel Canonical Correlation Analysis o kfa() : Kernel Feature Analysis o sigest() : Hyperparameter estimation for the Gaussian and the Laplacian kernels o inchol() : Incomplete Cholesky decomposition method o csi() : Cholesky decompositi...

...o rvm() : Relevance Vector Machines for regression o specc() : Spectral Clustering o kkmeans() : Kernel k-means clustering o ranking() : Kernel-based ranking method o onlearn() : Kernel-based Online Learning algorithms for classification, novelty detection and regression o kpca() : Kernel Pricipal Components Analysis o kcca() : Kernel Canonical Correlation Analysis o kfa() : Kernel Feature Analysis o sigest() : Hyperparameter estimation for the Gaussian and the Laplacian kernels o inchol() : Incomplete Cholesky decomposition method o csi() : Cholesky decompositi...