similar to: a possible bug in svmlight (PR#8012)

Hi ! Right now I am learning to use svm functions available in R and trying to use these function with given example. I was stuck with svmlight function which is available in klaR package. Any help would be appreciated regarding this function. 1. I am unable to use svmlight( ) which is available in package: klaR. Although I have downloaded klaR_0.6-3 package from

Dear R Users, When I used svmlight, I got below error: my command is: foo <- svmlight(y~., data= myData) the results: Error in file(con, "r") : unable to open connection In addition: Warning messages: 1: svm_learn not found 2: cannot open file '_model_1.txt' > myData[1:2,] y X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 1 1 63 1 0 0 145 233 1 1 0

Hi! I got the following runtime error when I tried to use svm method with stepclass. Error in "colnames<-"(`*tmp*`, value = c("0", "1")) : attempt to set colnames on object with less than two dimensions I repeated the same sequence of statements but this time I used the classification function used in the example, i.e., "lda" and it worked fine

Hello, We have a system which creates thousands of regression/classification models and in cases where we have only one input variable NaiveBayes throws an error. Maybe I am mistaken and I shouldn't expect to have a model with only one input variable. We use R version 2.6.0 (2007-10-03). We use caret (v4.1.19), but have tested similar code with klaR (v.0.5.8), because caret relies on

I am refering to a function call like this: >data(iris) >x <- svmlight(Species ~ ., data = iris) I tried to see the content of it by typing: > Species ~ . but it gives nothing. How can I see it's content ? - P.Dubois

Hi, I run R 2.10.1 under ubuntu 10.04 LTS (Lucid Lynx) and klaR version 0.6-4. I compute a model over a 2 classes dataset (composed of 700 examples). To that aim, I use the function NaiveBayes provided in the package klaR. When I then use the prediction function : predict(my_model, new_data). I get the following warning : "In FUN(1:747[[747L]], ...) : Numerical 0 probability with

Hi All I am having 2 very long character strings (550chars) and I want to put them as expressions together with c(). The problem is that I also get these double-quotes, as seen below in 'fct'. How can I remove these double-quotes? I tried as.name() but it did not work (because of size?). These are creating trouble with subsequent programs, which I tested with strings that for some

Dear All, Would you please tell me how to display the sample No. on the map ? ---Below commands don't display the sample No.(from 1 to 150).--- library(som) library(klaR) iris.som3 <- som(iris[,1:4], xdim = 14,ydim = 6) library(klaR); opar<- par(xpd = NA) shardsplot(iris.som3, data.or = iris,label = TRUE) legend(3.5,14.3, col = rainbow(3), xjust =0.5, yjust = 0,legend =

Dear all, I have a data frame in which the columns need to be ordered. The first column X is at the right position, but the remaining columns X1-Xn should be ordered like this: X1, X2, X3 etc instead of like below. > colnames(pos1) [1] "X" "X1" "X10" "X11" "X12" "X13" "X14" "X15" "X16"

Hi R-experts, Does anyone have experience using R for handling large scale data (millions of rows, hundreds or thousands of features)? What is the largest size of data that anyone has used with glm? Also, is there a library to read data in sparse data format (like SVMlight format)? Thanks Pradheep [[alternative HTML version deleted]]

I use Windows, R version 2.5.1 When I try to run stepclass (klaR) I get an error message/warning saying: 1: error(s) in modeling/prediction step in: cv.rate(vars = c(model, tryvar), data = data, grouping = grouping, ... Actually, I look 16 warnings of this type. Can anyone tell me what this means? Also, it returns only 2 out of the 79 variables as important, however these variables

Dear all, I have monthly data in wide format, I am only providing data (at the bottom of the email) for the first 24 columns but I have 2880 columns in total. I would like to take max of every 12 columns. I have taken the mean of every 12 columns with the following code: byapply <- function(x, by, fun, ...) { # Create index list if (length(by) == 1) { nc <- ncol(x)

Hi I want to create a nice picture about my result of k -the nearest neighbours algorithm. Here is my easy code: ################################# library(klaR) library(ipred) library(mlbench) data(PimaIndiansDiabetes2) dane=na.omit(PimaIndiansDiabetes2)[,c(2,5,9)] dane[,2]=log(dane[,2]) dane[,1:2]=scale(dane[,1:2]) zbior.uczacy=sample(1:nrow(dane),nrow(dane)/2,F)

This is what I was looking for. Thank you everyone! Sincerely, Milu <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail> Mail priva di virus. www.avast.com <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail>

Dear all, I am trying to do a n-fold cross-validation for a regularized discrimant function analysis using rda from the package klaR. However, I have problems to predict the groups from the test/validation sample. The exmaples of the R documantation and some online webpage also do not work. Does anybody know what I have done wrong? Here my code # I want to use the first 6 observations for

Dear all, I have a question on the shardsplot package:klaR(see the below Example). Plese tell me the meanings of " logstand <- t((t(logcount) / sdlogcount) * c(1,2,6,5,5,3))", much more. Why does this example use "c(1,2,6,5,5,3)" ? Examples: # Compute clusters and an Eight Directions Arranged Map for the # country data. Plotting the result.

Hi.. i have an expression of the form: model1<-nls(y~beta1*(x1+(k1*x2)+(k1*k1*x3)+(k2*x4)+(k2*k1*x5)+(k2*k2*x6)+(k3*x7)+(k3*k4*x8)+(k3*k2*x9)+(k3*k3*x10)+ (k4*x11)+(k4*k1*x12)+(k4*k2*x13)+(k4*k3*x14)+(k4*k4*x15)+(k5*x16)+(k5*k1*x17)+(k5*k2*x18)+(k5*k3*x19)+

Hi Milu, byapply(df, 12, function(x) apply(x, 1, max)) You might also be interested in the matrixStats package. Best, Ista On Tue, Feb 20, 2018 at 9:55 AM, Miluji Sb <milujisb at gmail.com> wrote: > Dear all, > > I have monthly data in wide format, I am only providing data (at the bottom > of the email) for the first 24 columns but I have 2880 columns in total. > > I

Hi All, I've encountered an issue where tail merging MIs is causing a problem with the post-RA MI scheduler dependency analysis and I'm not sure of the best way to address the problem. In my case, the branch folding pass (lib/CodeGen/BranchFolding.cpp) is merging common code from BB#14 and BB#15 into BB#16. It's clear that there are 4 common instructions (marked with an *) in BB#14

Ista, et. al: efficiency? (Note: I needed to correct my previous post: do.call() is required for pmax() over the data frame) > x <- data.frame(matrix(runif(12e6), ncol=12)) > system.time(r1 <- do.call(pmax,x)) user system elapsed 0.049 0.000 0.049 > identical(r1,r2) [1] FALSE > system.time(r2 <- apply(x,1,max)) user system elapsed 2.162 0.045 2.207 ##