similar to: e1071 tune.control() random parameter

Might not be the best place to ask, but i could get lucky.. I have setup an eclipse environment to write sweave files lately and wanted to switch to knitr. I could get it to work on easy files, but my earlier written sweave file fails to be knit properly. Here is the error message: Quitting from lines 273-276: Error in setwd(base.dir) : kann Arbeitsverzeichnis nicht wechseln (it says: cannot

Hi everyone I have banking data set in long format with 4 columns.One of these columns is bank name which consist of 49 banks and I want the data for only 40 banks out of these 49 so can anyone help me on how to get this 40 banks data My data looks like Year Name totalliabilties assets 1990 a 90 10 1991 a 89 48 1992 a 87

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 R-Help! I've looked around and have not found: A simple(short) way to hide functions and variables from the global environment. What i want is for a few of them to only be accessable from the scriptfile they're in. I probably could do fun things with environments , but that seems quite a hassle. As example: I have a file that gets me stuff from the database and creates an R object

Can i somehow append objects to an .Rdata file? I didn't see an option for it in the save() method. dump() won't work since i have s4 objects in there.

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Hi! If i found a problem with the code of one of the libraries (not core), or, in my current case, would wish something minor changed for convenience, where can i get contact? Can i put it in the "official" bug repository? (Problem discription for anyone interested: Why call the default function kpca for a matrix with kpar=list(sigma=0.2), instead of putting this default sigma into the

Following problem: Say you have a bunch of parameters and want to produce results for all combinations of those: height<-c("high","low") width<-c("slim","wide") then what i used to do was something like this: l<-list() for(h in height){ l[[h]]<-list() for(w in width){ l[[h]][[w]] <- doSomething() } } Now those parameters aren't

Hi All, I need to normalize/scale string variable which represents interests of customers (e.g., 'cycling, rollerblading, swimming' etc). Does anybody know how to do this, I want then use it along with other numeric variables for SVM classification. Appreciate for any advice. -Alex [[alternative HTML version deleted]]

Hi! how do i get to the source code of kpca or even better predict.kpca(which it tells me doesn't exist but should) ? (And if anyone has too much time: Now if i got that right, the @pcv attribute consists of the principal components, and for kpca, these are defined as projections of some random point x, which was transformed into the other feature space -> f(x), projected onto the actual

Hi! I am getting a lot of numbers in the background of the pca screeplots if i use call("plot") and eval(somecall). Til now, creating the calls and plotting later on this way worked fine. Example: pcaI<-prcomp(iris[,1:4]) plot(pcaI) x<-call("plot",pcaI) eval(x) Anyone got an idea how i can avoid that? (also it might take a second or so for the numbers to appear,

I'm making tables for prediction results of classifiers (2 classes) that show the usual numbers, true positives, false positives, etc I used the command table(predictedLabels,realLabels) to make those. I just had a case though ,where one of the label vectors had only one class in it. This will result in only half a table. Compare: x<-c(1,1,1,0,0) y<-c(1,1,1,0,1) table(x,y) to

Everyone, I'm very new to R, especially when it comes to loops and functions, so please bear with me if this is an elementary question. I cannot seem to figure out how to construct a loop which runs a function until a certain value is computed. For example, say I have the following: num = numeric (10) num [1] = 0 for (i in 2:10) { num [i] = num [i-1] + 5 } This adds 5 to the

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Hello, I have an SVM model previously calibrated using libsvm R implementation from the e1071 package. I would like to use this SVM to predict values, from a Java program. I first tried to use jlibsvm and the "standard" java implementation of libsvm, without success. Thus, I am now considering writing data in files from my Java code, calling an R program to predict values, then gather

Dear all, I am currently looking for a book about support vector machines for regression and classification and am a bit lost since they are plenty of books dealing with this subject. I am not totally new to the field and would like to get more information on that subject for later use with the e1071 <http://cran.r-project.org/web/packages/e1071/index.html> package for instance. Does

Hi All, In package e1071 for SVM based classification, one can get a probability measure for each prediction. I like to know what is method that is used for calculating this probability. Is it calculated using logistic link function? Thanks for your help. Regards, Raj

Dear David, Dear Friends, After any running svm I receive different results of Error estimation of 'svm' using 10-fold cross validation. What is the reason ? It is caused by the algorithm, libsvm , e1071 or something els? Which value can be optimal one ? How much run can reach to the optimality.And finally, what is difference between Error estimation of svm using 10-fold cross validation

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

Hi, the new version 1.1-0 of package e1071 is now on CRAN. Changes: *) use libsvm 2.1 for support vector machines. We are now also a kind of ``official'' R frontend to libsvm and linked from their homepage at http://www.csie.ntu.edu.tw/~cjlin/libsvm *) new functions for comparing partitions Best, Fritz -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-