R: Class rules - A Set of Rules

rules-class {arules} | R Documentation

## Class rules — A Set of Rules

### Description

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 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

coerce

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

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. Technically this method produces the same as the result of method `items()`, but wrapped into an `itemsets` object with support information.

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`

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.

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`

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)

nitems

  `signature(x = "rules")`; number of all possible items in the binary matrix representation of the object.

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)

summary

  `signature(object = "rules")`

### Author(s)

Michael Hahsler

### See Also

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

### Examples

    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 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 = " ---> ")

[Package arules version 1.6-2 Index]