similar to: e1071 ver 1.5-27 and older - SVM bug report

** save image Error in loadNamespace(i[[1]], c(lib.loc, .libPaths()), keep.source) : There is no package called 'class' Using 30 May 2004 developer version of R-1.9.0 trying URL `http://cran.r-project.org/src/contrib/e1071_1.4-0.tar.gz' Content type `application/x-tar' length 325388 bytes opened URL .......... .......... .......... .......... .......... ..........

Hi, I'm encountering trouble compiling caTools_1.17.1.tar.gz and e1071_1.6-4.tar.gz on a Linux system using the Intel compiler suite. 14 other packages I generally use installed without any trouble. I notice both of these trouble packages have a C++ component, so I wonder if that might be the issue. Below, there's information on my platform, compiler, and some diagnostic output showing

Hi Martyn, Thanks for your insight, that seems pretty direct. Unfortunately, I did not compile this version of R (it's on a large supercomputer system and this version of R was installed by the admins). Using "R CMD config", I see the following relevant settings: DYLIB_LD = icc -std=gnu99 DYLIB_LDFLAGS = -shared -openmp LDFLAGS = -L/opt/compilers/intel/cce/9.1.039/lib

I observed the same behavior as Edward this morning with R-1.2.2 on Red Hat Linux 7.0. There appears to be a problem with the library in netpbm-9.5-5, even after hunting down the missing shhopt.h that pbmplus.h is looking for. I worked around the problem by compiling e1071 without pbm support (moved pbm.c to pbm.c.bak). Matt Matthew R. Nelson, Ph.D. Director, Information Systems Esperion

I observed the same behavior as Edward this morning with R-1.2.2 on Red Hat Linux 7.0. There appears to be a problem with the library in netpbm-9.5-5, even after hunting down the missing shhopt.h that pbmplus.h is looking for. I worked around the problem by compiling e1071 without pbm support (moved pbm.c to pbm.c.bak). Matt Matthew R. Nelson, Ph.D. Director, Information Systems Esperion

Hi list, Could someone help me to explain why the leave-one-out cross validation results I got from svm using the internal option "cross" are different from those I got manually? It seems using "cross" to do cross validation, the results are always better. Please see the code below. I also include lda as a comparison. I'm using WinXP, R-2.9.0, and e1071_1.5-19. Many

Hello, I'm using recursive SVM script (rSVM - http://www.stanford.edu/group/wonglab/RSVMpage/R-SVM.html ) on some microarray data. The data to be input are log2, as numeric matrix w/ attributes -- str(svm_num_mat) num [1:10, 1:12340] 13.1 13.1 13.1 13.1 13.0 ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:10] "rma_log2_con_sample_1"

In R 1.9.0 running under Solaris 2.9 on a SunBlade 100, with "Sun WorkShop 6 update 2 C++ 5.3 2001/05/15" as the C++ compiler, I just did > install.packages("e1071") The output includes these lines, which I have wrapped to fit nicely in mail: ** libs cc -I/users/local/lib/R/include -I/usr/local/include -KPIC -xlibmil \ -dalign -xO4 -c cmeans.c -o cmeans.o cc

I am trying to implement a simple r-svm example using the iris data (only two of the classes are taken and data is within the code). I am running into some errors. I am not an expert on svm's. If any one has used it, I would appreciate their help. I am appending the code below. Thanks../Murli ####################################################### ### R-code for R-SVM ### use leave-one-out

On Tue, 2015-04-21 at 11:46 -0600, Andy Jacobson (NOAA Affiliate) wrote: > Hi, > > I'm encountering trouble compiling caTools_1.17.1.tar.gz and > e1071_1.6-4.tar.gz on a Linux system using the Intel compiler suite. > 14 other packages I generally use installed without any trouble. I > notice both of these trouble packages have a C++ component, so I > wonder if that might

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Hi, If I try to read the codes of functions in e1071 package, it gives me following error message. >library(e1071) > svm function (x, ...) UseMethod("svm") <environment: namespace:e1071> > predict.svm Error: Object "predict.svm" not found > Can someone help me on this how to read the codes of the functions in the e1071 package? Thanks. Raj

Hi, I ran two svm models in R e1071 package: the first without cross-validation and the second with 10-fold cross-validation. I used the following syntax: #Model 1: Without cross-validation: > svm.model <- svm(Response ~ ., data=data.df, type="C-classification", > kernel="linear", cost=1) > predict <- fitted(svm.model) > cm <- table(predict,

Hi all, I've got the following error message in using e1071 svm routine... Could anybody please help me? Thank you! --------------------------------- model <- svm(y=factor(mytraindata[, 1]), x=mytraindata[, -1], probability=T) Error in if (any(co)) { : missing value where TRUE/FALSE needed In addition: Warning message: In FUN(newX[, i], ...) : NAs introduced by coercion

Full_Name: Noel O'Boyle Version: 2.1.0 OS: Debian GNU/Linux Sarge Submission from: (NULL) (131.111.8.96) (1) Description of error The 10-fold CV option for the svm function in e1071 appears to give incorrect results for the rmse. The example code in (3) uses the example regression data in the svm documentation. The rmse for internal prediction is 0.24. It is expected the 10-fold CV rmse

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), :

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

Dear all, after having calibrated a svm model through the svm() command of the e1071 package, is there a way to i) represent the modeled relationships between the y and X variables (response variable vs. predictors)? ii) rank the influence of the predictors used in the model? Right now I am more interested in regression models, but I guess this would be useful for classification too. Thank

Hi, I ran two svm models in R e1071 package: the first without cross-validation and the second with 10-fold cross-validation. I used the following syntax: #Model 1: Without cross-validation: > svm.model <- svm(Response ~ ., data=data.df, type="C-classification", > kernel="linear", cost=1) > predict <- fitted(svm.model) > cm <- table(predict,

In e1071 package/svm default epsilon value is set to 0.1 and not 0.5 as documentation says. R