fim4r {arules}R Documentation

Interface to Mining Algorithms from fim4r


Interfaces the algorithms implemented in fim4r. The algorithms include: Apriori, Eclat, FPgrowth, Carpenter, IsTa, RElim and SaM.


  method = NULL,
  target = "frequent",
  support = 0.1,
  confidence = 0.8,
  originalSupport = TRUE,
  appear = NULL,
  report = NULL,
  verbose = TRUE,



a transactions object


the algorithm to be used. One of:

  • "apriori", "eclat", "fpgrowth" can mine itemsets and rules.

  • "relim", "sam" can mine itemsets.

  • "carpenter", "ista" can only mine closed itemset.


the target type. One of: "frequent", "closed", "maximal", "generators" or "rules".


a numeric value for the minimal support in the range [0,1].


a numeric value for the minimal confidence of rules in the range [0,1].


logical; Use the support threshold on the support of the whole rule (LHS and RHS). If FALSE, then LHS support (i.e., coverage) is used by the support threshold.


Specify item appearance in rules (only for apriori, eclat, fpgrowth and the target "rules") Specify a list with two vectors (item labels and appearance modifiers) of the same length. Appearance modifiers are:

  • "-" (item may not appear in a rule),

  • "a" (item may only appear a rule antecedent/LHS),

  • "c" (item may only appear a rule consequent/RHS),

  • "x" (item may appear anywhere).


cannot be used via the interface.


logical; print used parameters?


further arguments are passed on to the function the fim4r::fim4r function for the given method. Examples are: zmin, zmax, wgts.


Installation: The package fim4r is not available via CRAN. If needed, the fim4r() function downloads and installs the current version of the package automatically. Your system needs to have build tools installed.

Build tools: You need to be able to install source packages. For Windows users this means that you need to install the RTools with a version matching your R version.

Additional Notes:


An object of class itemsets or rules.


Christian Borgelt, fimi4r: Frequent Item Set Mining and Association Rule Induction for R.

See Also

Other mining algorithms: APappearance-class, AScontrol-classes, ASparameter-classes, apriori(), eclat(), ruleInduction(), weclat()


## Not run: 

# list available algorithms

# mine association rules with FPgrowth
r <- fim4r(Adult, method = "fpgrowth", 
  target = "rules", supp = .7, conf = .8)
inspect(head(r, by = "lift"))

# mine closed itemsets with Carpenter or IsTa
fim4r(Adult, method = "carpenter", 
  target = "closed", supp = .7)
fim4r(Adult, method = "ista", 
  target = "closed", supp = .7)

# mine frequent itemset of length 2 (zmin and zmax = 2)
freq_2 <- fim4r(Adult, method = "relim", target = "frequent", supp = .7,
  zmin = 2, zmax = 2)

# mine maximal frequent itemsets
mfis <- fim4r(Adult, method = "sam", target = "maximal", supp = .7)

# Examples for how to use item appearance with apriori, eclat, 
#   fpgrowth in fim4r. We first mine all rules.
inspect(fim4r(Adult, method = "fpgrowth", 
  target = "rules", supp = .8))

# ignore item "capital-gain=None"
inspect(fim4r(Adult, method = "fpgrowth", 
  target = "rules", supp = .8,
  appear = list(c("capital-gain=None"), c("-"))))

# "capital-gain=None" cannot appear in consequent (antecedent only)
inspect(fim4r(Adult, method = "fpgrowth", 
  target = "rules", supp = .8,
  appear = list(c("capital-gain=None"), c("a"))))

# "capital-gain=None" cannot appear in the antecedent
inspect(fim4r(Adult, method = "fpgrowth", 
  target = "rules", supp = .8,
  appear = list(c("capital-gain=None"), c("c"))))

# restrict the consequent to the item "capital-gain=None".
# That is, "" = all items can only appear in the antecedent with the 
# exception that "capital-gain=None" can only appear in the consequent.
inspect(fim4r(Adult, method = "fpgrowth", 
  target = "rules", supp = .8,
  appear = list(c("", "capital-gain=None"), c("a", "c"))))

## End(Not run)

[Package arules version 1.7-7 Index]