Displaying 20 results from an estimated 8000 matches similar to: "kernlab version 0.9-7"
2006 Nov 27
0
kernlab 0.9-0 on CRAN
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()
2006 Nov 27
0
kernlab 0.9-0 on CRAN
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()
2011 May 28
0
how to train ksvm with spectral kernel (kernlab) in caret?
Hello all,
I would like to use the train function from the caret package to
train a svm with a spectral kernel from the kernlab package. Sadly
a svm with spectral kernel is not among the many methods in caret...
using caret to train svmRadial:
------------------
library(caret)
library(kernlab)
data(iris)
TrainData<- iris[,1:4]
TrainClasses<- iris[,5]
set.seed(2)
2009 Oct 04
3
error installing/compiling kernlab
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"
2010 Sep 24
0
kernlab:ksvm:eps-svr: bug?
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
2008 Jun 25
1
stringdot
Hi!!
I am trying to figure out how to use the string kernel "stringdot" in kernlab.
k <- function(x,y) {
(sum(x*y) +1)*exp(-0.001*sum((x-y)^2))
}
class(k) <- "kernel"
data(promotergene)
## train svm using custom kernel
gene.k <- ksvm(Class~.,data=promotergene,kernel=k,C=10,cross=5) # works fine in this case
gene.rbf <-
2008 Jul 29
0
stringdot ?
Dear all,
I am using kernlab package in R, and I have amino acid sequences with different lenghts as input for a SVM and I need to go through this sequences using windows (sliding or fixed) of size X.
Does anyone has any suggestions about which function I should use?
I thought I could use stringdot, but I am not sure whether it will do what I need.., I have defined my stringdot as:
mystringdot
2010 Nov 09
1
library(kernlab) --- unable to load shared library
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
2007 Dec 17
0
kernlab and gram matrix
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.
2007 Oct 30
0
kernlab/ ksvm: class.weights & prob.model in binary classification
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),
2010 Nov 22
2
R package "kernlab" can not be properly loaded
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?
2013 Nov 03
1
Failed to install kernlab package
Hi everyone,
I am trying to install kernlab package, but failed many times by now on
CentOS 6 operating system. FYI, I have no problem with this package
installation on windows platform.
Here is the error message:
trying URL 'http://cran.wustl.edu/src/contrib/kernlab_0.9-18.tar.gz'
Content type 'application/x-gzip' length 1069148 bytes (1.0 Mb)
opened URL
2009 Apr 28
1
kernlab - custom kernel
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 ~ .,
2012 Sep 13
0
I need help for svm package kernlab in R
I use the svm package kernlab .I have two question.
In R
library(kernlab)
m=ksvm(xtrain,ytrain,type="C-svc",kernel=custom function, C=10)
alpha(m)
alphaindex(m)
I can get alpha value and alpha index about package.
1.
Assumption that number of sample are 20.
number of support vectors are 15.
then rest 5`s alphas are 0?
2. I want use kernelMatrix
xtrain=as.matrix(xtrain)
2012 Aug 27
0
kernlab`s custom kernel of ksvm freeze
Hello, together
I'm trying to use user defined kernel. I know that kernlab offer user
defined kernel(custom kernel functions) in R.
I used data spam including package kernlab.
(number of variables=58 number of examples =4061)
i'm user defined kernel's form,
kp=function(d,e){
as=v*d
bs=v*e
cs=as-bs
cs=as.matrix(cs)
exp(-(norm(cs,"F")^2)/2)
}
2012 Nov 29
1
Help with this error "kernlab class probability calculations failed; returning NAs"
I have never been able to get class probabilities to work and I am relatively new to using these tools, and I am looking for some insight as to what may be wrong.
I am using caret with kernlab/ksvm. I will simplify my problem to a basic data set which produces the same problem. I have read the caret vignettes as well as documentation for ?train. I appreciate any direction you can give. I
2006 Nov 24
1
How to find AUC in SVM (kernlab package)
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
2008 Aug 27
1
R 2.7.2 kernlab issues
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
2013 Apr 03
1
kernlab::kkmeans initial centers
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
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2005 Mar 17
1
kernlab sigest
hello,
I have the following problem setting parameter 'frac' in the sigest
function of the kernlab package.
## executing the ?sigest example:
library(kernlab)
data(spam)
srange <- sigest(type~.,data = spam)
## works fine...
## setting 'frac' explicitly
## (in this case even to the default of .25)
options(error=recover)
srange <- sigest(type~.,data = spam, frac = .25)
##