# test_that("convertOMLRunToBMR", {
# with_test_cache({
# class.tasks = lapply(c(19, 20), getOMLTask)
# regr.tasks = lapply(c(631, 632), getOMLTask)
#
# # ## Supervised Classification with predict.type = "response"
# # run.class = lapply(class.tasks, function(x) runTaskMlr(x, makeLearner("classif.rpart", predict.type = "response")))
# # run.class.ids = sapply(run.class, function(x) uploadOMLRun(x, tags = "convertBMR"))
# # ## Supervised Classification tasks with different estimation procedures
# # run.class.prob = lapply(class.tasks, function(x) runTaskMlr(x, makeLearner("classif.rpart", predict.type = "prob")))
# # run.class.prob.ids = sapply(run.class.prob, function(x) uploadOMLRun(x, tags = "convertBMR"))
# # ## Supervised Regression
# # run.regr = lapply(regr.tasks, function(x) runTaskMlr(x, makeLearner("regr.rpart")))
# # run.regr.ids = sapply(run.regr, function(x) uploadOMLRun(x, tags = "convertBMR"))
#
# ### Supervised Classification tasks with different estimation procedures
# run.class.list = lapply(c(219, 220), getOMLRun)
# bmr = lapply(run.class.list, convertOMLRunToBMR, measures = "area_under_roc_curve")
# for (i in 1:length(bmr)) {
# checkBMR(bmr[[i]])
# expect_equal(bmr[[i]]$measures[[1]]$id, "auc")
# expect_error(getPredictionProbabilities(getBMRPredictions(bmr[[i]])[[1]][[1]]), "Probabilities not present")
# }
# expect_s3_class(mlr::mergeBenchmarkResults(bmr), "BenchmarkResult")
#
# ### Supervised Classification with predict.type = "response"
# run.class.prob.list = lapply(c(221, 222), getOMLRun)
# bmr = lapply(run.class.prob.list, convertOMLRunToBMR, measures = "area_under_roc_curve")
# for (i in 1:length(bmr)) {
# checkBMR(bmr[[i]])
# expect_data_frame(getPredictionProbabilities(getBMRPredictions(bmr[[i]])[[1]][[1]]))
# }
# expect_s3_class(mlr::mergeBenchmarkResults(bmr), "BenchmarkResult")
#
# ### Supervised Regression
# run.regr.list = lapply(c(223, 224), getOMLRun)
# bmr = lapply(run.regr.list, convertOMLRunToBMR, measures = "root_mean_squared_error")
# for (i in 1:length(bmr)) {
# checkBMR(bmr[[i]])
# }
# expect_s3_class(mlr::mergeBenchmarkResults(bmr), "BenchmarkResult")
# })
# })
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