Running 'testthat.R' [23s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > library("testthat")
  > library("arulesCBA")
  Loading required package: Matrix
  Loading required package: arules
  
  Attaching package: 'arules'
  
  The following objects are masked from 'package:base':
  
      abbreviate, write
  
  
  Attaching package: 'arulesCBA'
  
  The following object is masked from 'package:arules':
  
      rules
  
  > 
  > testthat::test_check("arulesCBA")
  Apriori
  
  Parameter specification:
   confidence minval smax arem  aval originalSupport maxtime support minlen
          0.8    0.1    1 none FALSE           FALSE       5    0.01      1
   maxlen target  ext
        5  rules TRUE
  
  Algorithmic control:
   filter tree heap memopt load sort verbose
      0.1 TRUE TRUE  FALSE TRUE    2    TRUE
  
  Absolute minimum support count: 1 
  
  set item appearances ...[14 item(s)] done [0.00s].
  set transactions ...[14 item(s), 120 transaction(s)] done [0.00s].
  sorting and recoding items ... [14 item(s)] done [0.00s].
  creating transaction tree ... done [0.00s].
  checking subsets of size 1 2 3 4 5 done [0.00s].
  writing ... [79 rule(s)] done [0.00s].
  creating S4 object  ... done [0.00s].
  CBA Classifier Object
  Formula: Species ~ .
  Number of rules: 6
  Default Class: NA
  Classification method: first  
  Description: CBA algorithm (Liu et al., 1998)
  
  Accuracy: 0.96 
  
  CBA Classifier Object
  Formula: Species ~ .
  Number of rules: 9
  Default Class: setosa
  Classification method: weighted  - using best 5 rules
  Description: FOIL-based classifier (Yin and Han, 2003)
  
  Accuracy: 0.953 
  
  CBA Classifier Object
  Formula: Species ~ .
  Number of rules: 9
  Default Class: NA
  Classification method: logit  
  Description: RCAR+ based on RCAR (Azmi et al., 2019)
  
  Accuracy: 0.96 
  
  CBA Classifier Object
  Formula: Species ~ .
  Number of rules: 4
  Default Class: setosa
  Classification method: first  
  Description: RWeka classifier weka/classifiers/rules/JRip
  
  Accuracy: 0.953 
  
  CBA Classifier Object
  Formula: Species ~ .
  Number of rules: 5
  Default Class: setosa
  Classification method: first  
  Description: RWeka classifier weka/classifiers/rules/PART
  
  Accuracy: 0.967 
  
  CBA Classifier Object
  Formula: Species ~ .
  Number of rules: 3
  Default Class: setosa
  Classification method: first  
  Description: RWeka classifier weka/classifiers/trees/J48
  
  Accuracy: 0.96 
  
  CBA Classifier Object
  Formula: Species ~ .
  Number of rules: 6
  Default Class: NA
  Classification method: first  
  Description: CBA algorithm (Liu et al., 1998)
  
  Accuracy: 0.96 
  
  CBA Classifier Object
  Formula: Species ~ .
  Number of rules: 9
  Default Class: setosa
  Classification method: weighted  - using best 5 rules
  Description: FOIL-based classifier (Yin and Han, 2003)
  
  Accuracy: 0.953 
  
  CBA Classifier Object
  Formula: Species ~ .
  Number of rules: 9
  Default Class: NA
  Classification method: logit  
  Description: RCAR+ based on RCAR (Azmi et al., 2019)
  
  Accuracy: 0.96 
  
  CBA Classifier Object
  Formula: Species ~ .
  Number of rules: 4
  Default Class: setosa
  Classification method: first  
  Description: RWeka classifier weka/classifiers/rules/JRip
  
  Accuracy: 0.953 
  
  CBA Classifier Object
  Formula: Species ~ .
  Number of rules: 5
  Default Class: setosa
  Classification method: first  
  Description: RWeka classifier weka/classifiers/rules/PART
  
  Accuracy: 0.967 
  
  CBA Classifier Object
  Formula: Species ~ .
  Number of rules: 3
  Default Class: setosa
  Classification method: first  
  Description: RWeka classifier weka/classifiers/trees/J48
  
  Accuracy: 0.96 
  
  == Failed tests ================================================================
  -- Error (test-classifiers.R:49:3): (code run outside of `test_that()`) --------
  Error in `base::rowSums(x, na.rm = na.rm, dims = dims, ...)`: 'x' must be an array of at least two dimensions
  Backtrace:
      x
   1. \-arulesCBA:::cl(f, dat) test-classifiers.R:49:2
   2.   \-arulesCBA::pruneCBA_M1(formula, rulebase, trans)
   3.     +-methods:::rowSums(rhss[class_ids, ])
   4.     \-methods:::rowSums(rhss[class_ids, ])
   5.       \-base::rowSums(x, na.rm = na.rm, dims = dims, ...)
  
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 10 ]
  Error: Test failures
  Execution halted