| rules-class {arules} | R Documentation |
The rules class represents a set of rules.
Note that the class can also represent a multiset of rules with duplicated
elements. Duplicated elements can be removed with unique.
Objects are the result of calling the function apriori.
Objects can also be created by calls of the form
new("rules", ...).
lhs:Object of class
itemMatrix;
the left-hand-sides of the rules (antecedents)
rhs:Object of class
itemMatrix;
the right-hand-sides of the rules (consequents)
quality:a data.frame
Class associations, directly.
signature(from = "rules", to = "data.frame");
represents the set of rules as a data.frame
signature(object = "rules");
returns the whole item information data frame including item
labels
signature(object = "rules");
returns the item labels used to encode the rules
signature(x = "rules");
returns for each rule the union of the items in the
lhs and rhs (i.e., the itemsets
which generated the rule) as an
itemMatrix
signature(x = "rules");
returns a collection of the itemsets which generated the rules (one
itemset for each rule). Note that the collection can be a multiset and
contain duplicated
elements. Use unique to remove duplicates and obtain a
proper set.
signature(object = "rules");
returns labels for the rules ("lhs => rhs") as a
character vector. The representation can be customized using
the additional parameter ruleSep and parameters for label
defined in itemMatrix
signature(object = "rules");
returns the item labels as a character vector.
The index for each label is the column index of the item in the
binary matrix.
signature(x = "rules");
returns the itemMatrix
representing the left-hand-side of the rules (antecedents)
signature(x = "rules");
replaces the itemMatrix
representing the left-hand-side of the rules (antecedents)
signature(x = "rules");
returns the itemMatrix
representing the right-hand-side of the rules (consequents)
signature(x = "rules");
replaces the itemMatrix
representing the right-hand-side of the rules (consequents)
signature(object = "rules")
Michael Hahsler
[-methods,
apriori,
c,
duplicated,
inspect,
length,
match,
sets,
size,
subset,
associations-class,
itemMatrix-class,
data("Adult")
## Mine rules.
rules <- apriori(Adult, parameter = list(support = 0.4))
## Select a subset of rules using partial matching on the items
## in the right-hand-side and a quality measure
rules.sub <- subset(rules, subset = rhs %pin% "sex" & lift > 1.3)
## Display rules.
inspect(sort(rules.sub)[1:3])