similar to: kernlab sigest

A recent message on ansari.test() prompted me to play with the examples. This doesn't work for me in R version 2.4.1 R> ansari.test(rnorm(100), rnorm(100, 0, 2), conf.int = TRUE) Error in uniroot(ab, srange, tol = 1e-04, zq = qnorm(alpha/2, lower = FALSE)) : object "ab" not found It looks like there's a small typo in ccia() inside ansari.test.default() in which

A new version of kernlab has just been released. kernlab is a kernel-based Machine Learning package for R. kernlab includes the following functions: o ksvm() : Support Vector Machines for classification, regression, novelty detection, native multi-class classification, support for class-probability output and confidence intervals in regression. o gausspr()

A new version of kernlab has just been released. kernlab is a kernel-based Machine Learning package for R. kernlab includes the following functions: o ksvm() : Support Vector Machines for classification, regression, novelty detection, native multi-class classification, support for class-probability output and confidence intervals in regression. o gausspr()

Hello list, I am faced with a two-class classification problem with highly asymetric class sizes (class one: 99%, class two: 1%). I'd like to obtain a class probability model, also introducing available information on the class prior. Calling kernlab/ksvm with the line > ksvm_model1<-ksvm(as.matrix(slides), as.factor(Class), class.weights= c("0" =99, "1" =1),

Hi there, I'm trying to do a regression experiment on a multidimensional dataset where both x and y in the model are multidimensional vectors. I'm using R version 2.9.2, updated packages, on a Linux box. I've tried gausspr(), ksvm() and rvm(), and the models are computed fine, but I'm always getting the same error message when I try to use predict(): "Error in

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"

Hi, A. In a nutshell: The training error, obtained as "error (ret)", from the return value of a ksvm () call for a eps-svr model is (likely) being computed wrongly. "nu-svr" and "eps-bsvr" suffer from this as well. I am attaching three files: (1) ksvm.R from the the kernlab package, un-edited, (2) ksvm_eps-svr.txt: (for easier reading) containing only eps-svr

Hi all, I've analyzed the packet stream resulting from a SIP session through Asterisk, and I found that Asterisk sends a lot of useless messages! In example, it repeats the three way handshake (invite-ok-ack) every time, also when it has just to forward the 'bye' message. Has anyone found the same srange thing? thanks..

Hi all, Got a srange problem and wondered if anyone could shed some light on it. Have set up Samba but I cant log in from a windows workstation (get a message saying that either the password is incorrect or access was denied). I have set all the users up and Linux users (red hat 7.2) and as smb user (had to do this manually though as smbpasswd -a didnt copy them across) and both users accounts

Full_Name: Wei Xu Version: 1.5.1 OS: WindowsME Submission from: (NULL) (63.215.238.92) The P-value for a two.sided test is not consistent with the confidence interval. For example, P-value=0.1372, but the 95% CI doesn't include the H0 value(1). > x [1] 0.80 0.83 1.89 1.04 1.45 1.38 1.91 1.64 0.73 1.46 > y [1] 1.15 0.88 0.90 0.74 1.21 >

Hi, My question might be a little general. I have a number of values to select for the complexity parameters in some classifier, e.g. the C and gamma in SVM with RBF kernel. The selection is based on which values give the smallest cross validation error. I wonder if the randomized splitting of the available dataset into folds is done only once for all those choices for the parameter values, or

When compiling samba-3.0.7 on Redhat-7.2, stock kernel 2.4.26, I get undefined references: ------- Compiling libads/ads_status.c with -fPIC Linking nsswitch/libnss_wins.so lib/system.po: In function `sys_dlopen': lib/system.po(.text+0xc17): undefined reference to `dlopen' lib/system.po: In function `sys_dlsym': lib/system.po(.text+0xc3b): undefined reference to `dlsym'

hi All, I have a srange problem. Before dovecot there was a courier imap and it worked just fine. The client(s) are the same then before, so I think, this is an server side problem. I have a user with Outlook and he uses pop3 and leaves messages on server. Sometimes the messages get downloaded again, when he starts the outlook. Not all, but 7-9 hours back. uidl format is like it's

Hi, I tried to load the package "kernlab" under R-v11 and R-v10, however it gave error message: Error in library.dynam(lib, package, package.lib) : shared library 'kernlab' not found In addition: Warning message: package 'kernlab' was built under R version 2.12.0 Error: package/namespace load failed for 'kernlab' Has anybody loaded this successfully before?

Dear R users, I have recently encountered a problem with using the function `library` in order to load the package `kernlab`. My output of sessionInfo() is as follows: R version 2.10.1 (2009-12-14) x86_64-unknown-linux-gnu locale: [1] C attached base packages: [1] stats graphics grDevices utils datasets methods base I have installed the package by

hi, I am using R's "kernlab" package, exactly i am doing classification using ksvm(.) and predict.ksvm(.).I want use of custom kernel. I am getting some error. # Following R code works (with promotergene dataset): library("kernlab") s <- function(x, y) { sum((x*y)^1.25) } class(s) <- "kernel" data("promotergene") gene <- ksvm(Class ~ .,

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.

Dear all, I was wondering if someone can help me. I am learning SVM for classification in my research with kernlab package. I want to know about classification performance using Area Under Curve (AUC). I know ROCR package can do this job but I found all example in ROCR package have include prediction, for example, ROCR.hiv {ROCR}. My problem is how to produce prediction in SVM and to find

Hello, After upgrading to 2.7.2 this morning via the cran repository, I get the following error when calling R via the command line: Error in dyn.load(file, DLLpath = DLLpath, ...) : unable to load shared library '/home/jstumpf/R/i486-pc-linux-gnu-library/2.7/kernlab/libs/kernlab.so': libRlapack.so: cannot open shared object file: No such file or directory Fatal error: unable to

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]]