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raidinfo
2012 May 15
1
caret: Error when using rpart and CV != LOOCV
Hy,
I got the following problem when trying to build a rpart model and using
everything but LOOCV. Originally, I wanted to used k-fold partitioning,
but every partitioning except LOOCV throws the following warning:
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Warning message: In nominalTrainWorkflow(dat = trainData, info =
trainInfo, method = method, : There were missing values in resampled
performance measures.
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Below are some simplified testcases which repoduce the warning on my
system.
Question: What does this error mean? How can I avoid it?
System-Information:
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> sessionInfo()
R version 2.15.0 (2012-03-30)...
2013 Mar 06
1
CARET and NNET fail to train a model when the input is high dimensional
The following code fails to train a nnet model in a random dataset using
caret:
nR <- 700
nCol <- 2000
myCtrl <- trainControl(method="cv", number=3, preProcOptions=NULL,
classProbs = TRUE, summaryFunction = twoClassSummary)
trX <- data.frame(replicate(nR, rnorm(nCol)))
trY <- runif(1)*trX[,1]*trX[,2]^2+runif(1)*trX[,3]/trX[,4]
trY <-
2013 Nov 15
1
Inconsistent results between caret+kernlab versions
I'm using caret to assess classifier performance (and it's great!). However, I've found that my results differ between R2.* and R3.* - reported accuracies are reduced dramatically. I suspect that a code change to kernlab ksvm may be responsible (see version 5.16-24 here: http://cran.r-project.org/web/packages/caret/news.html). I get very different results between caret_5.15-61 +