similar to: informal conventions/checklist for new predictive modeling packages

Hello, This is perhaps more of a regression question than R, but I am learning both, so would appreciate your wisdom here. I have some data which reflects power load for an electrical generating system, with some temporal features. The data fields look like this: D,MON,DAY,YR,HR,WDAY,DRYBULB,WETBULB,LOAD 4455 5 13 92 13 4 70 63 1617 4456 3 9 92 13 2 73

Aren't Friday's wonderful! I've just been hit up with a request from management to install Samba on our Solaris 8 UNIX servers to share out information to the windows PC's. This wouldn't be an issue if the backend was Windows AD but in our case it's eDirectory. The shares also need to be seamlessly accessible to eDirectory based groups/users without interfering with the

Dear All, Can anybody please refer to Asterisk / Linux server maintenance checklist or tutorial ? Regards, -- Kashif Naeem Business Development Manager Hadi Telecom www.haditelecom.com Cell: +92 (0)345 4226006 Office: +92 (0)42 32801143 Email: kashif at haditelecom.com MSN: kashif__naeem at hotmail.com Gmail: meet.kashif at gmail.com Skype: kashif.naeem -------------- next part

Hi guys, Here's what I'm doing: Upgrading fro Samba 2.2.8a to Samba 3.0.2a Simultaneously migrating to a new server. My checklist: << (*)=done , (-) = remaining >> * Download and install Samba 3.0.2a on the new server * Clone (by hand) hostname, sldapd, nssswitch * Hand edit new smb.conf to match the old config. * Export ldif file from old LDAP db * Dump old Domain SID

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"

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 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?

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 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

Hello list. I'm thinking to migrate the hole user db from system users to mysql. I already did it in a test environment, but something is annoying my OCD... I don't quote the variables username and password sent to the mysql server. I know, the mysql user that dovecot uses only has select rights, but it stills bother me, because its possible to do an useless sql code injection. Is there a

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 ~ .,

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

Greetings, everybody I've browsed around a bit, but there seems to be no single practical list of this kind. What would you do to make a new Centos server which must run apache, IMAP (Dovecot) and SMTP (PostFix) and nothing else for a few domains as secure from attacks as possible, using only standard RPM packages as much as possible? (Please note that choice of other IMAP and SMTP servers

Hi, I compiled Samba 3.0.23d on a CentOS 4.4 machine. Then I configured /etc/krb5.conf for my domain. Was able to successfully run kinit and join my Windows 2003 domain with a net ads join. Net ads user and net ads group returns the users and the groups of the domain. So far so good. I'm kinda stuck on the next step. I would like to grant access to the share defined in smb.conf to anybody

Dear R-community, I was using SVM regression (svm {e1071}) for predictions of single soil properties of a huge data set (3000 samples). There are for the eps-regression using the radial basis kernel three optimization parameters needed. To make things easier (using only two optimization parameters and not loosing performance) I wanted to use LS SVM regression (lssvm{kernlab}). But it

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

Hi all, Does anyone know how to debug S4 methods? In my case I want to find an error in the specc-function of the kernlab-package. As this seems to be a S4-method the normal S3 debugging can't be applied apparently (e.g. debug(s3function.someclass)). So in my case > debug(specc:kernlab) seems only to debug the generic-function: > specc:kernlab function (x, ...)

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