CRAN Package Check Results for Package RMOA

Last updated on 2025-12-05 20:49:02 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.1.0 6.19 65.62 71.81 NOTE
r-devel-linux-x86_64-debian-gcc 1.1.0 4.19 38.68 42.87 ERROR
r-devel-linux-x86_64-fedora-clang 1.1.0 12.00 97.31 109.31 OK
r-devel-linux-x86_64-fedora-gcc 1.1.0 12.00 105.82 117.82 OK
r-devel-windows-x86_64 1.1.0 7.00 85.00 92.00 OK
r-patched-linux-x86_64 1.1.0 5.49 60.63 66.12 OK
r-release-linux-x86_64 1.1.0 5.64 62.85 68.49 OK
r-release-macos-arm64 1.1.0 OK
r-release-macos-x86_64 1.1.0 6.00 90.00 96.00 OK
r-release-windows-x86_64 1.1.0 6.00 86.00 92.00 OK
r-oldrel-macos-arm64 1.1.0 OK
r-oldrel-macos-x86_64 1.1.0 4.00 76.00 80.00 OK
r-oldrel-windows-x86_64 1.1.0 6.00 148.00 154.00 OK

Check Details

Version: 1.1.0
Check: CRAN incoming feasibility
Result: NOTE Maintainer: ‘Jan Wijffels <jwijffels@bnosac.be>’ Package CITATION file contains call(s) to old-style personList() or as.personList(). Please use c() on person objects instead. Package CITATION file contains call(s) to old-style citEntry(). Please use bibentry() instead. Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc

Version: 1.1.0
Check: examples
Result: ERROR Running examples in ‘RMOA-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: predict.MOA_trainedmodel > ### Title: Predict using a MOA classifier, MOA regressor or MOA recommender > ### on a new dataset > ### Aliases: predict.MOA_trainedmodel > > ### ** Examples > > ## Hoeffdingtree > hdt <- HoeffdingTree(numericEstimator = "GaussianNumericAttributeClassObserver") > data(iris) > ## Make a training set > iris <- factorise(iris) > traintest <- list() > traintest$trainidx <- sample(nrow(iris), size=nrow(iris)/2) > traintest$trainingset <- iris[traintest$trainidx, ] > traintest$testset <- iris[-traintest$trainidx, ] > irisdatastream <- datastream_dataframe(data=traintest$trainingset) > ## Train the model > hdtreetrained <- trainMOA(model = hdt, + Species ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width, + data = irisdatastream) > > ## Score the model on the holdoutset > scores <- predict(hdtreetrained, + newdata=traintest$testset[, c("Sepal.Length","Sepal.Width","Petal.Length","Petal.Width")], + type="response") > str(scores) chr [1:75] "setosa" "setosa" "setosa" "setosa" "setosa" "setosa" "setosa" ... > table(scores, traintest$testset$Species) scores setosa versicolor virginica setosa 22 0 0 versicolor 0 28 2 virginica 0 2 21 > scores <- predict(hdtreetrained, newdata=traintest$testset, type="votes") > head(scores) setosa versicolor virginica [1,] 2.1116956 5.814254e-24 3.626837e-23 [2,] 1.0692703 3.750871e-24 4.501561e-24 [3,] 0.9214671 1.344403e-22 2.681703e-23 [4,] 2.0708417 7.756787e-25 1.596365e-23 [5,] 2.3213611 8.046016e-23 9.878775e-23 [6,] 0.2389012 1.283804e-23 3.152946e-24 > > ## Prediction based on recommendation engine > require(recommenderlab) Loading required package: recommenderlab Warning in library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : there is no package called ‘recommenderlab’ > data(MovieLense) Warning in data(MovieLense) : data set ‘MovieLense’ not found > x <- getData.frame(MovieLense) Error in getData.frame(MovieLense) : could not find function "getData.frame" Execution halted Flavor: r-devel-linux-x86_64-debian-gcc