search for: 36x4393

...nal) independence of margins in a contingency table. Happy drawing! David, Achim, Kurt -- Dr. David Meyer Department of Information Systems and Operations Vienna University of Economics and Business Administration Augasse 2-6, A-1090 Wien, Austria, Europe Fax: +43-1-313 36x746 Tel: +43-1-313 36x4393 HP: http://wi.wu-wien.ac.at/~meyer/ _______________________________________________ R-packages mailing list R-packages at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-packages

...en welcome! David, Achim, Kurt. PS: If you like modern art, try out demo(mondrian)! :) -- Dr. David Meyer Department of Information Systems and Operations Vienna University of Economics and Business Administration Augasse 2-6, A-1090 Wien, Austria, Europe Fax: +43-1-313 36x746 Tel: +43-1-313 36x4393 HP: http://wi.wu-wien.ac.at/~meyer/ _______________________________________________ R-packages mailing list R-packages at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-packages

Hello, I am using SVM under e1071 package for nu-regression with 18 parameters. The variables are ordered factors, factors, date or numeric datatypes. I use the linear kernel. It gives the following error that I cannot solve. I tryed debug, browser and all that stuff, but no way. The error is: Error in get(ctr, mode = "function", envir = parent.frame())(levels(x), :

Hello, if I try to tune my svm with the code: Tune <- tune.svm(Data.Train, Class.Train, type="C-classification", kernel="radial", gamma = 2^(-1:1), cost = 2^(2:4)) i get a windows Messagebox with a error in the application "Rgui.exe" and the message: "Die Anweisung in 0x6c48174d verweist auf Speicher 0x00000000. Der Vorgang "read" konnte nicht auf

Dear All , 1- I'm trying to access the values of fitted(model) after model<- tune.svm( ) but seemingly it is not poosible. How can I access to values of fitted ? However ,it is possible only after model<- svm( ) 2- How can I access to the other values such as the number of Support Vectors , gamma, cost , nu , epsilon , after model<- tune.svm( ) ? these are not possible? I

...nal) independence of margins in a contingency table. Happy drawing! David, Achim, Kurt -- Dr. David Meyer Department of Information Systems and Operations Vienna University of Economics and Business Administration Augasse 2-6, A-1090 Wien, Austria, Europe Fax: +43-1-313 36x746 Tel: +43-1-313 36x4393 HP: http://wi.wu-wien.ac.at/~meyer/ _______________________________________________ R-packages mailing list R-packages at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-packages

Dear All, I have such a two-class problem, one class is very large(~98% of total), and the other is just 2%. According to manual of nnet, I need setup "weights", so I intend to set 1 for class one, 49 for class 2. How do I do that? Just weights=49? Meanwhile I'd like to try svm(e1071), again, how do I setup "class.weights"? Thanks. BTW: Many thanks to Jake and Uwe for

Dear David, Dear R Users , Suppose that we want to regress for example a certain autoregressive model using SVM. We have our data and also some fixed kernels in libSVM behinde e1071 in front. The question: Where can we insert our certain autoregressive model ? During creating data frame ? Or perhaps we can make a relationship between our variables ended to desired autoregressive model ?

...en welcome! David, Achim, Kurt. PS: If you like modern art, try out demo(mondrian)! :) -- Dr. David Meyer Department of Information Systems and Operations Vienna University of Economics and Business Administration Augasse 2-6, A-1090 Wien, Austria, Europe Fax: +43-1-313 36x746 Tel: +43-1-313 36x4393 HP: http://wi.wu-wien.ac.at/~meyer/ _______________________________________________ R-packages mailing list R-packages at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-packages

Dear All, I've a question about scaling the input variables for an analysis with svm (package e1071). Most of my variables are factors with 4 to 6 levels but there are also some numeric variables. I'm not familiar with the math behind svms, so my assumtions maybe completely wrong ... or obvious. Will the svm automatically expand the factors into a binary matrix? If I add numeric

I am using SVM to classify categorical data and I would like the probabilities instead of the classification. ?predict.svm says that its only enabled when you train the model with it enabled, so I did that, but it didn't work. I can't even get it to work with iris. The help file shows that probability = TRUE when training the model, but doesn't show an example. Then I try to

Dear R people, I am trying to plot the results from running svm in library(e1071). I use plot.svm. After searching through the help archives and FAQ, I still have several questions: 1. In default, crosses indicate support vectors. But why are there two colors of crosses? What do they represent? 2. I want to draw a white-gray colored plot and modify the different colored crosses or circles by

Hi. I'm trying to plot a pair of intertwined spirals and an svm that separates them. I'm having some trouble. Here's what I tried. > library(mlbench) > library(e1071) Loading required package: class > raw <- mlbench.spirals(200,2) > spiral <- data.frame(class=as.factor(raw$classes), x=raw$x[,1], y=raw$x[,2]) > m <- svm(class~., data=spiral) > plot(m,

Dear all, I'm a trainee statistician in a company and we'd like to understand svm mechanism, at first with simple examples. I use e1071 package and I have several questions. I'm working with data extracted from cats data (from R). My dataset corresponds to a completely separable case with a binary response variable ( Sex with 2 levels: F and M), two explanatory variables (Bwt

Hi I am doing this sort of thing: POLY: > > obj = best.tune(svm, similarity ~., data = training, kernel = "polynomial") > summary(obj) Call: best.tune(svm, similarity ~ ., data = training, kernel = "polynomial") Parameters: SVM-Type: eps-regression SVM-Kernel: polynomial cost: 1 degree: 3 gamma: 0.04545455 coef.0: 0