search for: kkmean

Hi, I am trying to pass initial cluster assignments to the kkmeans method<http://rss.acs.unt.edu/Rdoc/library/kernlab/html/kkmeans.html>of kernlab. It is not clear to me how I can set the parameter *centers* with "initial cluster centers" as stated in the documentation? thanks, --ahmed [[alternative HTML version deleted]]

Hi, I have a very large dataset of 3008 individuals and 800 numerical variables. In fact it is a table of 3008 36-monthes multivariated time series that I would like to classify with an unsupervised algorithm I had a look at the function kkmeans of e1071 package, which seems to be a kernel weighted version of the algorithm algorithm, and the bclust from the same package which does bootstrapping of kmean algorithm (bagging) I had the idea of combining these two functions, in fact using kkmeans in bclust parameters. What should I do ? Redu...

...obability output and confidence intervals in regression. o gausspr() : Gaussian Processes for classification and regression o lssvm() : Least Squares Support Vector Machines for classification 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...

...obability output and confidence intervals in regression. o gausspr() : Gaussian Processes for classification and regression o lssvm() : Least Squares Support Vector Machines for classification 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...

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"