search for: train_data

...function(.col){ all(is.na(.col)) || all(.col[1L] == .col) }) dataset <- dataset[!same] This works GREAT (thanks to the r-users list archive I found this) however, then when I do my data sampling like so: testSize <- floor(nrow(x) * 10/100) test <- sample(1:nrow(x), testSize) train_data <- x[-test,] test_data <- x[test, -1] test_class <- x[test, 1] It is now possible that test_data or train_data contain columns that are constants, however as one dataset they did not. So the solution for me is to just re-run lines to remove all constants......not a problem, but is this n...

Hi, I have a process using svm from the e1071 library. it works. I want to try using the KSVM library instead. The same data used wiht e1071 gives me an error with KSVM. My data is a data.frame. sample code: svm_formula <- formula(y ~ a + B + C) svm_model <- ksvm(formula, data=train_data, type="C-svc", kernel="rbfdot", C=1) I get the following error: "object is not a matrix" So I tried this: svm_model <- ksvm(formula, data=as.matrix(train_data), type="C-svc", kernel="rbfdot", C=1, scaled=FALSE) Now I get this error: "...

Hi, I am reading in a dataframe from a CSV file. It has 70 columns. I do not have any kind of unique "row id". rawdata <- read.table("r_work/train_data.csv", header=T, sep=",", na.strings=0) When training an svm, I keep getting an error So, as an experiment, I wrote the data back out to a new file so that I could see what the svm function sees. write.table(rawdata, file="r_work/output_data.csv", quote=FALSE, sep=&quot...

I have a data matrix with genes as columns and samples as rows. I want to create all possible gene ratios.Is there an elegant and fast way to do it in R and write it to a dataframe? Thanks for any help. Som. -- View this message in context: http://r.789695.n4.nabble.com/Calculating-all-possible-ratios-tp4627405.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML