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Hello. I want to use "for". I have a matrix called "mat" that has got 100 rows. I want to take the line 1 and make a1<-which(mat[1,]==1) After this I want to take the second row and make a2<-which(mat[2,]==1) and so on until I arrive at row 100. I want to make it automatic for the 100 rows and so I wrote: for(i in 1:nrow(mat)){ ai<-which(mat[i,]==1) }

Hello, I have 12 sample each sample has got 1000 observation, i.e I have a matrix X with 1000 rows and 12 columns! m <- svm(t(X)) p <- predict (m) Can anyone tell me how to use svmtrain() in R! Many Yhanks, Samuel [[alternative HTML version deleted]]

Hi, I am running an R script from the command line by calling: > R --vanilla < test.R My terminal is part of the Xwin (Xterm) and there is a plot(1:10) command in the test.R script. This will not produce a grahic though. When I start R by calling R then plotting from the R command in the same xterm, I do get a graphic display. How do I create a xwin plot by calling R from the command

HI I'm need to run samba version 2.2.8 and 2 smbd / nnbd processes in a single machine with two separate smb.conf files . They will runs on individual interfaces and how can I do that ? Tried all means that I know off , but to no avail. Please help. Thanks & rgs amin ============================================================================== This message is for the named

I am developing an application that uses Eclipse framework on Windows. I have to call R from Java. I downloaded rJava package and installed it. I set the classpath in the Run Dialog in Eclipse to the directory where the JRI.jar is. I set the Path environmental variable to the directory where R.dll and jri.dll are. Yet when I run the rtest example (in jri/examples directory), I get the

http://bugzilla.mindrot.org/show_bug.cgi?id=800 Summary: reverse lookup solaris Product: Portable OpenSSH Version: -current Platform: UltraSparc OS/Version: Solaris Status: NEW Severity: minor Priority: P2 Component: sshd AssignedTo: openssh-bugs at mindrot.org ReportedBy: koen.maris at

As a java programmer, I'm having issue conceptualizing the following use case: Given an value, passed into a function, how do I pull out the lookup? Ie. A list of keys (key1, key2, key3) A list of values (val1,val2,val3) I want to write a function (or is there something built in?) such that Callit <- (thekey) { (magic happens here) Return value } Any ideas? Thanks a bunch!

Hola a todos, estoy intentendo cargar unos datos contenidos en una tabla de ACCESS, por lo que ejecuto los siguientes comandos dir<-"C:/Users/D/Desktop/" library(RODBC) cn<-odbcConnectAccess(paste(dir1,"datos.mdb",sep="")) pero me da el siguiente error Warning messages: 1: In odbcDriverConnect(con, ...) : [RODBC] ERROR: state IM002, code 0, message

Caveats and disclaimers: I am quite happy to undertake self-teaching if directed to a relevant prior posting and welcome such direction. I have programming and statistical training/experience which I would characterize as Masters level. Thank you for reading and replying to this post. It is very much appreciated. ---begin problem description I have a large data set that I have imported to R

If do: > library("e1071") > example(svm) I get: svm> data(iris) svm> attach(iris) svm> ## classification mode svm> # default with factor response: svm> model <- svm(Species ~ ., data = iris) svm> # alternatively the traditional interface: svm> x <- subset(iris, select = -Species) svm> y <- Species svm> model <- svm(x, y) svm>

> x <- train[,c( 2:18, 20:21, 24, 27:31)] > y <- train$out > > svm.pr <- svm(x, y, probability = TRUE, method="C-classification", kernel="radial", cost=bestc, gamma=bestg, cross=10) > > pred <- predict(svm.pr, valid[,c( 2:18, 20:21, 24, 27:31)], decision.values = TRUE, probability = TRUE) > attr(pred, "decision.values")[1:4,]

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

I am trying to understand what is the difference between linear and polynomial kernel: linear: u'*v polynomial: (gamma*u'*v + coef0)^degree It would seem that polynomial kernel with gamma = 1; coef0 = 0 and degree = 1 should be identical to linear kernel, however it gives me significantly different results for very simple data set, with linear kernel

Hi, I have a question about the parameter C (cost) in svm function in e1071. I thought larger C is prone to overfitting than smaller C, and hence leads to more support vectors. However, using the Wisconsin breast cancer example on the link: http://planatscher.net/svmtut/svmtut.html I found that the largest cost have fewest support vectors, which is contrary to what I think. please see the scripts

*Hi, *Does anyone know how can I show an *ROC curve for R-SVM*? I understand in R-SVM we are not optimizing over SVM cost parameter. Any example ROC for R-SVM code or guidance can be really useful. Thanks, Angel. [[alternative HTML version deleted]]

svm.fit<-svm(as.factor(out) ~ ., data=all_h, method="C-classification", kernel="radial", cost=bestc, gamma=bestg, cross=10) # model fitting svm.pred<-predict(svm.fit, hh, decision.values = TRUE, probability = TRUE) # find the probability, but can not find. attr(svm.pred, "probabilities") > attr(svm.pred, "probabilities") 1 0 1 0 0 2 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

Estimados Un día leí algo en el siguiente hipervínculo, pero nunca lo use. http://blog.revolutionanalytics.com/2015/06/using-hadoop-with-r-it-depends.html Javier Rubén Marcuzzi De: Carlos J. Gil Bellosta Enviado: miércoles, 9 de diciembre de 2015 14:33 Para: MªLuz Morales CC: r-help-es Asunto: Re: [R-es] SVM hadoop No, no correrán en paralelo si usas los SVM de paquetes como e1071. No

Dear all, I'm not able to solve easily the following simple problem. I really hope someone can give me some hints. I trained an svm (e1071). Now I'd like to show the results graphically. I used plot.svm and I'd like to add some other objects to the plot: points, (coloured) ellipses to indicate some intersting regions, curves, and so on... I tried to pass these as additional

Hi, I am studying using SVM functions of e1071 package to do prediction, and I found during the training data are "factor" type, then svm.predict() can predict data directly by categories; but if response variables are "numerical", the predicted value from svm will be continuous quantitative numbers, then how can I connect these quantitative numbers to categories? (for