Hello David, file not found should be the path problem I guess. I just forgot the pROC library, which I included here. These are all the libraries I am using.
library(caret) library(farff) library(DMwR) library(pROC) library(pls) setwd("C:/Users/PC/Documents") d=readARFF("bughunter.arff") dput( head( d, 30 ) ) index <- createDataPartition(d$`Bug class`, p = .70,list = FALSE) tr <- d[index, ] ts <- d[-index, ] boot3 <- trainControl(method = "repeatedcv", number=10, repeats=10,classProbs = TRUE,verboseIter = FALSE, summaryFunction = twoClassSummary, sampling = "rose") set.seed(30218) ct <- train(`Bug class` ~ ., data = tr, method = "pls", metric = "AUC", preProc = c("center", "scale", "nzv"), trControl = boot3) getTrainPerf(ct) <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail&utm_term=icon> Virus-free. www.avast.com <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail&utm_term=link> <#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2> On Thu, Jul 23, 2020 at 4:01 PM Neha gupta <neha.bologn...@gmail.com> wrote: > > Hello David, thanks for your reply. I have added the information. > > library(caret) > library(farff) > library(DMwR) > > d=readARFF("bughunter.arff") > dput( head( d, 30 ) ) > > index <- createDataPartition(d$`Bug class`, p = .70,list = FALSE) > > tr <- d[index, ] > > ts <- d[-index, ] > > boot3 <- trainControl(method = "repeatedcv", number=10, > repeats=10,classProbs = TRUE,verboseIter = FALSE, > > summaryFunction = twoClassSummary, sampling = "rose") > > set.seed(30218) > > ct <- train(`Bug class` ~ ., data = tr, method = "pls", metric = "AUC", > preProc > = c("center", "scale", "nzv"), trControl = boot3) > > getTrainPerf(ct) > > On Thu, Jul 23, 2020 at 1:08 AM David Winsemius <dwinsem...@comcast.net> > wrote: > >> >> On 7/22/20 3:43 PM, Neha gupta wrote: >> > Hello, >> > >> > >> > I get the following error when I use the ROSE class balancing method but >> > when I use other methods like SMOTE, up, down, I do not get any error >> > message. >> > >> > >> > Something is wrong; all the ROC metric values are missing: >> > >> > ROC Sens Spec >> > >> > Min. : NA Min. : NA Min. : NA >> > >> > 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA >> > >> > Median : NA Median : NA Median : NA >> > >> > Mean :NaN Mean :NaN Mean :NaN >> > >> > 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA >> > >> > Max. : NA Max. : NA Max. : NA >> > >> > >> > >> > library(DMwR) >> > >> > d=readARFF("bughunter.arff") >> >> After installing that package and loading pkg:DMwR I get: >> >> >> Error in readARFF("bughunter.arff") : could not find function "readARFF" >> >> >> Since you also posted in HTML, I suggest you read the Posting Guide, >> restart and R session and post a reproducible example that loads all >> needed packages and data. >> >> -- >> >> David. >> >> > >> > index <- createDataPartition(d$`Bug class`, p = .70,list = FALSE) >> > >> > tr <- d[index, ] >> > >> > ts <- d[-index, ] >> > >> > boot3 <- trainControl(method = "repeatedcv", number=10, >> > repeats=10,classProbs = TRUE,verboseIter = FALSE, >> > >> > summaryFunction = twoClassSummary, sampling = "rose") >> > >> > set.seed(30218) >> > >> > ct <- train(`Bug class` ~ ., data = tr, >> > >> > method = "pls", >> > >> > metric = "AUC", >> > >> > preProc = c("center", "scale", "nzv"), >> > >> > trControl = boot3) >> > >> > getTrainPerf(ct) >> > >> > [[alternative HTML version deleted]] >> > >> > ______________________________________________ >> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> > https://stat.ethz.ch/mailman/listinfo/r-help >> > PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> > and provide commented, minimal, self-contained, reproducible code. >> > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.