similar to: How to abort function execution after x-seconds

Hello all, I'm trying to run a gird parameter search for a svm. Therefore I'M using the ksvm function from the kernlab package. ---- svp <- ksvm(Ktrain,ytrain,type="nu-svc",nu=C) ---- The problem is that the optimization algorithm does not return for certain parameters. I tried to use setTimeLimit() but that doesn't seem to help. I suspect that ksvm() calls c code that

Hello, I am using kernlab to do some binary classification on aminoacid strings. I am using a custom kernel, so i use the kernel="matrix" option of the ksvm method. My (normalized) kernel matrix is of size 1309*1309, my results vector has the same length. I am using C-svc. My kernlab call is something similiar to this: ksvm(kernel="matrix", kernelMatrix, trainingDataYs,

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, I have a process using svm from the e1071 library. it works. I want to try using the KSVM library instead. The same data used wiht e1071 gives me an error with KSVM. My data is a data.frame. sample code: svm_formula <- formula(y ~ a + B + C) svm_model <- ksvm(formula, data=train_data, type="C-svc", kernel="rbfdot", C=1) I get the following error:

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 <-

Dear list, I am using the ksvm function from kernlab as follows: (1) learning > svm.pol4 <- ksvm(class.labs ~ ., data = train.data, prob.model = T, scale = T, kernel = "polydot") (2) prediction > svm.pol.prd4 <- predict(svm.pol4, train.data, type = "probabilities")[,2] But unfortunately, when calling the prediction, once in every 10s of times (using the exact

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

Hi useR's, I am resending this request since I got no response for my last post and I am new to the list so pardon me if I am violating the protocol. I am trying to use the "Kernlab" package for training and prediction using SVM's. I am getting the following error when I am trying to use the predict function: > predictSvm = predict(modelforSVM, testSeq); Error in

with pred.pca<-predict(splits[[i]]$pca,trainingData at samples)[,1:nPCs] dframe<-as.data.frame(cbind(pred.pca,class=isExplosive(trainingData,2))); results[[i]]$classifier<-ksvm(class~.,data=dframe,scaled=T,kernel="polydot",type="C-svc", C=C,kpar=list(degree=degree,scale=scale,offset=offset),prob.model=T) and a degree of 5 i get an error of 0 reported by the ksvm

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

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, I found a small problem with kernlab. The problem, I think, is that the 3-fold cross-validation performed to estimate probabilities is not class-balanced, so the classifier could find empty classes. The following example (maybe a little forced) show the error: data(glass) set.seed(1)

Hello together, I'm looking for advice on how to do some tests on strings. What I want to do is the following: (just an example, real strings/sequence are about 200-400 characters long) given set of Strings: String1 abcdefgh String2 bcdefgop use a sliding window of size x to create an vector of all subsequences of size x found in the set (order matters! ). Now create, for every string

Hi, Is it possible to calculate confidence intervals for support vector regression? In the "ksvm{kernlab}" manual, it says that it supports confidence intervals for regression. However, i couldn't find any information about how to calculate confidence interval. Do you have any documents or examples about this or any other suggestions? Thanks in advance -- [[alternative HTML

I'm using caret to assess classifier performance (and it's great!). However, I've found that my results differ between R2.* and R3.* - reported accuracies are reduced dramatically. I suspect that a code change to kernlab ksvm may be responsible (see version 5.16-24 here: http://cran.r-project.org/web/packages/caret/news.html). I get very different results between caret_5.15-61 +

Hey all, I'm trying to replicate some plots with ggplot2. The problem is that I need to specify the color for every attribute (drug). If I use the code below the colors get automatically assigned but I need to plot drug1 in black drug2 in blue etc. How do I do that? q = qplot(days,vol,data = cellLine7064, color = drug, geom = c("line", "point")) best regards, Immanuel

Hello all, I'm trying to use zoo.read but can't figure out how to deal with the time format. (example below) would be nice if someone could help. best regards, Immanuel --------------------------- L <- "Date,Time,Open,High,Low,Close,Up,Down 05.02.2001,00:30,421.20,421.20,421.20,421.20,11,0 05.02.2001,01:30,421.20,421.40,421.20,421.40,7,0

Hello List, I am having a great trouble using svm function in e1071 package. I have 4gb of data that i want to use to train svm. I am using Amazon cloud, my Amazon Machine Image(AMI) has 34.2 GB of memory. my R process was killed several times when i tried to use 4GB of data for svm. Now I am using a subset of that data and it is only 1.4 GB. i remove all unnecessary objects before calling

Hello all, I posted a questions on how to terminate a function call that does not return after a certain time ( I can not modify the function code) some time ago. Since I didn't find a solution I just came up with the idea to run the functions call in a separate thread who I could terminate a will. Would this be possible? Any pointers in the right direction? A looked briefly a snow and Rmpi

Hi, I'm working on a project using the kernlab library. For one phase, I want the "decision values" from the SVM prediction, not the class label. the e1071 library has this function, but I can't find the equivalent in ksvm. In general, when an SVM is used for classification, the label of an unknown test-case is decided by the "sign" of its resulting value as