Running examples in 'arc-Ex.R' failed
The error most likely occurred in:

> ### Name: predict.CBARuleModel
> ### Title: Apply Rule Model
> ### Aliases: predict.CBARuleModel
> 
> ### ** Examples
> 
>   allData<-datasets::iris[sample(nrow(datasets::iris)),]
>   trainFold <- allData[1:100,]
>   testFold <- allData[101:nrow(allData),]
>   #increase for more accurate results in longer time
>   target_rule_count <- 1000
>   classAtt <- "Species"
>   rm <- cba(trainFold, classAtt, list(target_rule_count = target_rule_count))
Running apriori with setting: confidence =  0.5 , support =  0 , minlen =  2 , maxlen =  3 , MAX_RULE_LEN =  5
Rule count:  81  Iteration:  1
Increasing maxlen to:   4
Running apriori with setting: confidence =  0.5 , support =  0 , minlen =  2 , maxlen =  4 , MAX_RULE_LEN =  5
Rule count:  371  Iteration:  2
Increasing maxlen to:   5
Running apriori with setting: confidence =  0.5 , support =  0 , minlen =  2 , maxlen =  5 , MAX_RULE_LEN =  5
Rule count:  977  Iteration:  3
Decreasing confidence to:   0.45
Running apriori with setting: confidence =  0.45 , support =  0 , minlen =  2 , maxlen =  5 , MAX_RULE_LEN =  5
Rule count:  978  Iteration:  4
Decreasing confidence to:   0.4
Running apriori with setting: confidence =  0.4 , support =  0 , minlen =  2 , maxlen =  5 , MAX_RULE_LEN =  5
Rule count:  979  Iteration:  5
Decreasing confidence to:   0.35
Running apriori with setting: confidence =  0.35 , support =  0 , minlen =  2 , maxlen =  5 , MAX_RULE_LEN =  5
Rule count:  979  Iteration:  6
Decreasing confidence to:   0.3
Running apriori with setting: confidence =  0.3 , support =  0 , minlen =  2 , maxlen =  5 , MAX_RULE_LEN =  5
Rule count:  984  Iteration:  7
Decreasing confidence to:   0.25
Running apriori with setting: confidence =  0.25 , support =  0 , minlen =  2 , maxlen =  5 , MAX_RULE_LEN =  5
Rule count:  986  Iteration:  8
Decreasing confidence to:   0.2
Running apriori with setting: confidence =  0.2 , support =  0 , minlen =  2 , maxlen =  5 , MAX_RULE_LEN =  5
Rule count:  987  Iteration:  9
Decreasing confidence to:   0.15
Running apriori with setting: confidence =  0.15 , support =  0 , minlen =  2 , maxlen =  5 , MAX_RULE_LEN =  5
Rule count:  989  Iteration:  10
Decreasing confidence to:   0.1
Running apriori with setting: confidence =  0.1 , support =  0 , minlen =  2 , maxlen =  5 , MAX_RULE_LEN =  5
Rule count:  997  Iteration:  11
Decreasing confidence to:   0.0500000000000001
Running apriori with setting: confidence =  0.0500000000000001 , support =  0 , minlen =  2 , maxlen =  5 , MAX_RULE_LEN =  5
Rule count:  1009  Iteration:  12
Target rule count satisfied:   1000
Removing excess discovered rules
Rule learning (incl. automatic threshold detection) took: 0.16  seconds
Original rules:  1000
Rules after data coverage pruning: 6
Performing default rule pruning.
Final rule set size:  6
Pruning took: 0.81  seconds
>   prediction <- predict(rm, testFold)
Warning in min(which(x == TRUE)) :
  no non-missing arguments to min; returning Inf
Warning in min(which(x == TRUE)) :
  no non-missing arguments to min; returning Inf
Warning in min(which(x == TRUE)) :
  no non-missing arguments to min; returning Inf
Warning in min(which(x == TRUE)) :
  no non-missing arguments to min; returning Inf
Warning in min(which(x == TRUE)) :
  no non-missing arguments to min; returning Inf
Warning in min(which(x == TRUE)) :
  no non-missing arguments to min; returning Inf
Warning in min(which(x == TRUE)) :
  no non-missing arguments to min; returning Inf
Warning in min(which(x == TRUE)) :
  no non-missing arguments to min; returning Inf
Warning in min(which(x == TRUE)) :
  no non-missing arguments to min; returning Inf
Warning in .translate_index(i, rownames(x), nrow(x)) :
  NAs introduced by coercion to integer range
Error in rule_model@rules@rhs[match] : invalid subscript(s)
Calls: predict ... lapply -> FUN -> [ -> [.data.frame -> which -> [ -> [
Execution halted