similar to: How to use a saved SVM model from e1071

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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

I am starting to use svm from e1071 and I wonder how exactly crossvalidation is implemented. Whenever I run > svm.model <- svm(y ~ ., data = trainset, cross = 3) on my data I get dirrerent values for svm.model$MSE e.g. [1] 0.9517001 1.7069627 0.6108726 [1] 0.3634670 0.9165497 1.4606322 This suggests to me that data are scrambled each time - the last time I looked at libsvm python

hii all!!! could anyone tell me how to use libsvm in R.. i am not able to find good way to use it.... -- View this message in context: http://r.789695.n4.nabble.com/about-libsvm-tp3007214p3007214.html Sent from the R help mailing list archive at Nabble.com.

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 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-

Hello, all experts, My major is computer-aied drug design ( main QSAR). Now, my paper need be reviesed, and one reviewer ask me do genetic algorithm coupled with gaussian process method (GA+GP). my data: training set: 191*106 test set: 73*106 here, I need use GA+GP to do variable selection when building the model. In R, there are not GA package like in matlab

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

I am accustomed to the LIBSVM package, which provides cross-validation on training with the -v option % svm-train -v 5 ... This does 5 fold cross validation while building the model and avoids over-fitting. But I don't see how to accomplish that in the e1071 package. (I learned that svm(... cross=5 ...) only _tests_ using cross-validation -- it doesn't affect the training.) Can

I have a bunch of data sets that were created for the libsvm tool. They are in "colon separated sparse format". i.e. 1 5:1 27:3 345:10 Is a row with the label of "1" and only has values in columns 5, 27, and 345. I want to read these into a data.frame in R. Is there a simple way to do this? -- Noah Silverman, M.S. UCLA Department of Statistics 8117 Math Sciences

Full_Name: Julien Gagneur Version: 2.2.1 OS: Linux (Suse 9.3) Submission from: (NULL) (194.94.44.4) Using the SparseM library (SparseM_0.66) and the e1071 library (e1071_1.5-12) I fail using svm method with a sparse matrix. Here is a sample example. I experienced the same problem under Windows. > library(SparseM) [1] "SparseM library loaded" > library("e1071")

A new version of e1071 has been released to CRAN which should be much easier to install on a lot of platforms because reading/writing PNM images has been moved to the pixmap package, hence there are no longer dependencies on external libraries and no configure mechanism. For the authors, Fritz Leisch ********************************************************** Changes in Version 1.2-0: o

I'm not sure what the parameter specifies: random if an integer value is specified, random parameter vectors are drawn from the parameter space. What are the parameter vectors and what is the parameter space? What means drawn? greetings Jessi [[alternative HTML version deleted]]

Dear all, I am trying to compile the package e1071 (version 1.3-11) with R CMD INSTALL. I tried with R 1.7.0 on Redhat Linux 2.4.7-10 and R 1.6.2 on Linux 2.4.9-34smp but keep getting the same error message during configure : WARNING: g++ 2.96 cannot reliably be used with this package. Please use a different compiler. Can anyone help me with this or at least point me in the right direction ?

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 ?

Hi-- While I agree that we cannot agree on the ideal algorithms, we should be taking practical steps to implement microarrays in the clinic. I think we can all agree that our algorithms have some degree of efficacy over and above conventional diagnostic techniques. If patients are dying from lack of diagnostic accuracy, I think we have to work hard to use this technology to help them, if we

I used the c binary svm-train in LIBSVM to create a model file. How do I load this model file into R? Is there a function in R package e1071 that accomplishes this operation? Thanks, Yin -- View this message in context: http://r.789695.n4.nabble.com/Loading-externally-created-LIBSVM-model-into-R-tp4407853p4407853.html Sent from the R devel mailing list archive at Nabble.com.

Hello, When calling several times the svm() function, I get different results. Do I miss something, or is there some random generation in the C library? In this second hypothesis, is it possible to fix an eventual seed? Thank you Pierre ### Example library('e1071') x = rnorm(100) # train set y = rnorm(100) c = runif(100)>0.5 x2 = rnorm(100)# test set y2 = rnorm(100) # learning a

Dear R Community- I am a new user of support vector machines for species distribution modeling and am using package e1071 to run svm() and predict.svm(). Briefly, I want to create an svm model for classification of a factor response (species presence or absence) based on climate predictor variables. I have used a training dataset to train the model, and tested it against a validation data set

Hello, I'm using nut to control a Belkin F6C1500-TW-RK ups (vendor ID 050d, product ID 0751). I'm using the belkin driver and a serial connection for communications. The host computer is running Debian. I have things configured such that both my computer and the ups shut off when the battery level reaches a critical level, and everything seems to work fine up to this point. My problem

Hello, I'm using nut to control a Belkin F6C1500-TW-RK ups (vendor ID 050d, product ID 0751). I'm using the belkin driver and a serial connection for communications. The host computer is running Debian. I have things configured such that both my computer and the ups shut off when the battery level reaches a critical level, and everything seems to work fine up to this point. My problem