CRAN Package Check Results for Package ipred

Last updated on 2026-08-02 02:50:27 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.9-15 9.85 118.86 128.71 ERROR
r-devel-linux-x86_64-debian-gcc 0.9-15 8.09 83.82 91.91 ERROR
r-devel-linux-x86_64-fedora-clang 0.9-15 18.00 178.30 196.30 ERROR
r-devel-linux-x86_64-fedora-gcc 0.9-15 88.48 ERROR
r-devel-windows-x86_64 0.9-15 16.00 137.00 153.00 ERROR
r-patched-linux-x86_64 0.9-15 11.38 108.43 119.81 ERROR
r-release-linux-x86_64 0.9-15 9.84 108.10 117.94 ERROR
r-release-macos-arm64 0.9-15 3.00 34.00 37.00 OK
r-release-macos-x86_64 0.9-15 9.00 144.00 153.00 OK
r-release-windows-x86_64 0.9-15 15.00 139.00 154.00 ERROR
r-oldrel-macos-arm64 0.9-15 OK
r-oldrel-macos-x86_64 0.9-15 8.00 124.00 132.00 OK
r-oldrel-windows-x86_64 0.9-15 19.00 167.00 186.00 ERROR

Check Details

Version: 0.9-15
Check: examples
Result: ERROR Running examples in ‘ipred-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: errorest > ### Title: Estimators of Prediction Error > ### Aliases: errorest errorest.data.frame errorest.default > ### Keywords: misc > > ### ** Examples > > > # Classification > > data("iris") > library("MASS") > > # force predict to return class labels only > mypredict.lda <- function(object, newdata) + predict(object, newdata = newdata)$class > > # 10-fold cv of LDA for Iris data > errorest(Species ~ ., data=iris, model=lda, + estimator = "cv", predict= mypredict.lda) Call: errorest.data.frame(formula = Species ~ ., data = iris, model = lda, predict = mypredict.lda, estimator = "cv") 10-fold cross-validation estimator of misclassification error Misclassification error: 0.02 > > data("PimaIndiansDiabetes", package = "mlbench") Warning in data("PimaIndiansDiabetes", package = "mlbench") : data set ‘PimaIndiansDiabetes’ not found > ## Not run: > ##D # 632+ bootstrap of LDA for Diabetes data > ##D errorest(diabetes ~ ., data=PimaIndiansDiabetes, model=lda, > ##D estimator = "632plus", predict= mypredict.lda) > ## End(Not run) > > #cv of a fixed partition of the data > list.tindx <- list(1:100, 101:200, 201:300, 301:400, 401:500, + 501:600, 601:700, 701:768) > > errorest(diabetes ~ ., data=PimaIndiansDiabetes, model=lda, + estimator = "cv", predict = mypredict.lda, + est.para = control.errorest(list.tindx = list.tindx)) Error: object 'PimaIndiansDiabetes' not found Execution halted Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 0.9-15
Check: for new files in some other directories
Result: NOTE Found the following files/directories: ‘~/tmp/scratch/Rtmp0w5VqW’ ‘~/tmp/scratch/Rtmp1IeKY7’ ‘~/tmp/scratch/Rtmp1RK9rI’ ‘~/tmp/scratch/Rtmp1zENjd’ ‘~/tmp/scratch/Rtmp2O3jMx’ ‘~/tmp/scratch/Rtmp2TTOZQ’ ‘~/tmp/scratch/Rtmp3Aclxf’ ‘~/tmp/scratch/Rtmp3xLO42’ ‘~/tmp/scratch/Rtmp4AEEIV’ ‘~/tmp/scratch/Rtmp4yh0jS’ ‘~/tmp/scratch/Rtmp5b9eXS’ ‘~/tmp/scratch/Rtmp7sHxun’ ‘~/tmp/scratch/Rtmp88WuQM’ ‘~/tmp/scratch/Rtmp8FA8lz’ ‘~/tmp/scratch/Rtmp98FGPK’ ‘~/tmp/scratch/Rtmp9ph580’ ‘~/tmp/scratch/Rtmp9zKotN’ ‘~/tmp/scratch/RtmpA7wM12’ ‘~/tmp/scratch/RtmpB2nGI7’ ‘~/tmp/scratch/RtmpBAriJM’ ‘~/tmp/scratch/RtmpBDkL5o’ ‘~/tmp/scratch/RtmpBt9iWi’ ‘~/tmp/scratch/RtmpCLdeMc’ ‘~/tmp/scratch/RtmpCZpIyG’ ‘~/tmp/scratch/RtmpCmbzSx’ ‘~/tmp/scratch/RtmpDFP8qm’ ‘~/tmp/scratch/RtmpDQf90C’ ‘~/tmp/scratch/RtmpEO4YJO’ ‘~/tmp/scratch/RtmpEeFNlN’ ‘~/tmp/scratch/RtmpEmqAOm’ ‘~/tmp/scratch/RtmpFOcqtf’ ‘~/tmp/scratch/RtmpFeiwoE’ ‘~/tmp/scratch/RtmpFqKR5O’ ‘~/tmp/scratch/RtmpG2zVxV’ ‘~/tmp/scratch/RtmpG70yEm’ 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Version: 0.9-15
Check: examples
Result: ERROR Running examples in ‘ipred-Ex.R’ failed The error most likely occurred in: > ### Name: errorest > ### Title: Estimators of Prediction Error > ### Aliases: errorest errorest.data.frame errorest.default > ### Keywords: misc > > ### ** Examples > > > # Classification > > data("iris") > library("MASS") > > # force predict to return class labels only > mypredict.lda <- function(object, newdata) + predict(object, newdata = newdata)$class > > # 10-fold cv of LDA for Iris data > errorest(Species ~ ., data=iris, model=lda, + estimator = "cv", predict= mypredict.lda) Call: errorest.data.frame(formula = Species ~ ., data = iris, model = lda, predict = mypredict.lda, estimator = "cv") 10-fold cross-validation estimator of misclassification error Misclassification error: 0.02 > > data("PimaIndiansDiabetes", package = "mlbench") Warning in data("PimaIndiansDiabetes", package = "mlbench") : data set ‘PimaIndiansDiabetes’ not found > ## Not run: > ##D # 632+ bootstrap of LDA for Diabetes data > ##D errorest(diabetes ~ ., data=PimaIndiansDiabetes, model=lda, > ##D estimator = "632plus", predict= mypredict.lda) > ## End(Not run) > > #cv of a fixed partition of the data > list.tindx <- list(1:100, 101:200, 201:300, 301:400, 401:500, + 501:600, 601:700, 701:768) > > errorest(diabetes ~ ., data=PimaIndiansDiabetes, model=lda, + estimator = "cv", predict = mypredict.lda, + est.para = control.errorest(list.tindx = list.tindx)) Error: object 'PimaIndiansDiabetes' not found Execution halted Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-release-windows-x86_64, r-oldrel-windows-x86_64