Running examples in ‘qCBA-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: sbrlModel2arcCBARuleModel
> ### Title: sbrlModel2arcCBARuleModel Converts a model created by 'sbrl' so
> ###   that it can be passed to qCBA
> ### Aliases: sbrlModel2arcCBARuleModel
> 
> ### ** Examples
> 
> if (! requireNamespace("rCBA", quietly = TRUE)) {
+   message("Please install rCBA to allow for sbrl model conversion")
+   return()
+ } else
+ {
+   library(rCBA)
+ }
> if (! requireNamespace("sbrl", quietly = TRUE)) {
+   message("Please install sbrl to allow for postprocessing of sbrl models")
+   return()
+ } else
+ {
+   library(sbrl)
+ }
>  #sbrl handles only binary problems, iris has 3 target classes - remove one class
> set.seed(111)
> allData <- datasets::iris[sample(nrow(datasets::iris)),]
> classToExclude<-"versicolor"
> allData <- allData[allData$Species!=classToExclude, ]
> # drop virginica level
> allData$Species <-allData$Species [, drop=TRUE]
> trainFold <- allData[1:50,]
> testFold <- allData[51:nrow(allData),]
> sbrlFixedLabel<-"label"
> origLabel<-"Species"
> 
> orignames<-colnames(trainFold)
> orignames[which(orignames == origLabel)]<-sbrlFixedLabel
> colnames(trainFold)<-orignames
> colnames(testFold)<-orignames
> 
> # to recode label to binary values:
> # first create dict mapping from original distinct class values to 0,1 
> origval<-levels(as.factor(trainFold$label))
> newval<-range(0,1)
> dict<-data.frame(origval,newval)
> # then apply dict to train and test fold
> trainFold$label<-dict[match(trainFold$label, dict$origval), 2]
> testFold$label<-dict[match(testFold$label, dict$origval), 2]
> 
> # discretize training data
> trainFoldDiscTemp <- discrNumeric(trainFold, sbrlFixedLabel)
> trainFoldDiscCutpoints <- trainFoldDiscTemp$cutp
> trainFoldDisc <- as.data.frame(lapply(trainFoldDiscTemp$Disc.data, as.factor))
> 
> # discretize test data
> testFoldDisc <- applyCuts(testFold, trainFoldDiscCutpoints, infinite_bounds=TRUE, labels=TRUE)
> 
> # learn sbrl model
> sbrl_model <- sbrl(trainFoldDisc, iters=30000, pos_sign="0", 
+                    neg_sign="1", rule_minlen=1, rule_maxlen=10, 
+                    minsupport_pos=0.10, minsupport_neg=0.10, 
+                    lambda=10.0, eta=1.0, alpha=c(1,1), nchain=10)
Eclat

parameter specification:
 tidLists support minlen maxlen            target   ext
    FALSE     0.1      1     10 frequent itemsets FALSE

algorithmic control:
 sparse sort verbose
      7   -2    TRUE

Absolute minimum support count: 2 

create itemset ... 
set transactions ...[5 item(s), 26 transaction(s)] done [0.00s].
sorting and recoding items ... [5 item(s)] done [0.00s].
creating bit matrix ... [5 row(s), 26 column(s)] done [0.00s].
writing  ... [23 set(s)] done [0.00s].
Creating S4 object  ... done [0.00s].
Eclat

parameter specification:
 tidLists support minlen maxlen            target   ext
    FALSE     0.1      1     10 frequent itemsets FALSE

algorithmic control:
 sparse sort verbose
      7   -2    TRUE

Absolute minimum support count: 2 

create itemset ... 
set transactions ...[5 item(s), 24 transaction(s)] done [0.00s].
sorting and recoding items ... [5 item(s)] done [0.00s].
creating bit matrix ... [5 row(s), 24 column(s)] done [0.00s].
writing  ... [23 set(s)] done [0.00s].
Creating S4 object  ... done [0.00s].

 *** caught segfault ***
address 0x1000015, cause 'memory not mapped'

Traceback:
 1: sbrl(trainFoldDisc, iters = 30000, pos_sign = "0", neg_sign = "1",     rule_minlen = 1, rule_maxlen = 10, minsupport_pos = 0.1,     minsupport_neg = 0.1, lambda = 10, eta = 1, alpha = c(1,         1), nchain = 10)
An irrecoverable exception occurred. R is aborting now ...
Segmentation fault