Running ‘run-base.R’ [397s/526s]
Running the tests in ‘tests/run-base.R’ failed.
Complete output:
  > library(testthat)
  > test_check("mlr", filter = "base_")
  Loading required package: mlr
  Loading required package: ParamHelpers
  
  Attaching package: 'rex'
  
  The following object is masked from 'package:testthat':
  
      matches
  
  
  Attaching package: 'BBmisc'
  
  The following object is masked from 'package:base':
  
      isFALSE
  
  
  RF-SRC:  *** ERROR *** 
  RF-SRC:  Y-var factor level in data inconsistent with number of levels indicated:           2          0
  RF-SRC:  Please Contact Technical Support.<simpleError in doTryCatch(return(expr), name, parentenv, handler): 
  RF-SRC:  The application will now exit.
  >
  ── 1. Error: filterFeatures (@test_base_generateFilterValuesData.R#17)  ────────
  An error has occurred in the grow algorithm.  Please turn trace on for further analysis.
  1: suppressWarnings(generateFilterValuesData(binaryclass.task)) at testthat/test_base_generateFilterValuesData.R:17
  2: withCallingHandlers(expr, warning = function(w) invokeRestart("muffleWarning"))
  3: generateFilterValuesData(binaryclass.task)
  4: lapply(filter, function(x) {
         x = do.call(x$fun, c(list(task = task, nselect = nselect), more.args[[x$name]]))
         missing.score = setdiff(fn, names(x))
         x[missing.score] = NA_real_
         x[match(fn, names(x))]
     })
  5: FUN(X[[i]], ...)
  6: do.call(x$fun, c(list(task = task, nselect = nselect), more.args[[x$name]]))
  7: (function (task, nselect, method = "permute", ...) 
     {
         assertChoice(method, choices = c("permute", "random", "anti", "permute.ensemble", 
             "random.ensemble", "anti.ensemble"))
         im = randomForestSRC::rfsrc(getTaskFormula(task), data = getTaskData(task), proximity = FALSE, 
             forest = FALSE, importance = method, ...)$importance
         if (inherits(task, "ClassifTask")) {
             ns = rownames(im)
             y = im[, "all"]
         }
         else {
             ns = names(im)
             y = unname(im)
         }
         setNames(y, ns)
     })(task = structure(list(type = "classif", env = <environment>, weights = NULL, blocking = NULL, 
         coordinates = NULL, task.desc = structure(list(id = "binary", type = "classif", 
             target = "Class", size = 208L, n.feat = c(numerics = 60L, factors = 0L, ordered = 0L, 
             functionals = 0L), has.missings = FALSE, has.weights = FALSE, has.blocking = FALSE, 
             has.coordinates = FALSE, class.levels = c("M", "R"), positive = "M", negative = "R", 
             class.distribution = structure(c(M = 111L, R = 97L), .Dim = 2L, .Dimnames = list(
                 c("M", "R")), class = "table")), class = c("ClassifTaskDesc", "SupervisedTaskDesc", 
         "TaskDesc"))), class = c("ClassifTask", "SupervisedTask", "Task")), nselect = 60L)
  8: randomForestSRC::rfsrc(getTaskFormula(task), data = getTaskData(task), proximity = FALSE, 
         forest = FALSE, importance = method, ...)
  9: stop("An error has occurred in the grow algorithm.  Please turn trace on for further analysis.")
  
  ══ testthat results  ═══════════════════════════════════════════════════════════
  OK: 3569 SKIPPED: 0 FAILED: 1
  1. Error: filterFeatures (@test_base_generateFilterValuesData.R#17) 
  
  Error: testthat unit tests failed
  Execution halted