# rules-class

0th

Percentile

##### Class rules --- A Set of Rules

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.

Keywords
classes
##### Objects from the Class

Objects are the result of calling the function apriori. Objects can also be created by calls of the form new("rules", ...).

##### Slots

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; typically contains measures like support, confidence and count (i.e., the absolute support count)

##### Extends

Class '>associations, directly.

##### Methods

% \item{[}{\code{signature(x = "rules")}; % extracts a subset of rules and the associated quality measures}
coerce

signature(from = "rules", to = "data.frame"); represents the set of rules as a data.frame

itemInfo

signature(object = "rules"); returns the whole item information data frame including item labels

itemLabels

signature(object = "rules"); returns the item labels used to encode the rules

items

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

generatingItemsets

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.

labels

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

itemLabels

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.

% \item{length}{\code{signature(x = "rules")}; % returns the number of rules stored in the the set}
lhs

signature(x = "rules"); returns the '>itemMatrix representing the left-hand-side of the rules (antecedents)

lhs<-

signature(x = "rules"); replaces the '>itemMatrix representing the left-hand-side of the rules (antecedents)

rhs

signature(x = "rules"); returns the '>itemMatrix representing the right-hand-side of the rules (consequents)

rhs<-

signature(x = "rules"); replaces the '>itemMatrix representing the right-hand-side of the rules (consequents)

%\item{subset}{\code{signature(x = "rules")}; % selects a subset using restrictions on the quality measures or on % the items present in the rules (see examples).}
summary

signature(object = "rules")

[-methods, apriori, c, duplicated, inspect, length, match, sets, size, subset, associations-class, itemMatrix-class,

##### Aliases
• rules-class
• rules
• summary.rules-class
• show,summary.rules-method
• coerce,rules,data.frame-method
• itemInfo,rules-method
• itemLabels,rules-method
• items,rules-method
• generatingItemsets
• generatingItemsets,rules-method
• labels,rules-method
• itemLabels,rules-method
• lhs<-,rules-method
• lhs,rules-method
• rhs<-,rules-method
• rhs,rules-method
• lhs<-
• lhs
• rhs<-
• rhs
• summary,rules-method
• initialize,rules-method
##### Examples
# NOT RUN {

## 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 the top 3 support rules
inspect(head(rules.sub, n = 3, by = "support"))

## Display the first 3 rules
inspect(rules.sub[1:3])

## Get labels for the first 3 rules
labels(rules.sub[1:3])
labels(rules.sub[1:3], itemSep = " + ", setStart = "", setEnd="",
ruleSep = " ---> ")
# }

Documentation reproduced from package arules, version 1.5-4, License: GPL-3

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