# sequencerules-class

0th

Percentile

##### Class "sequencerules" --- Collections of Sequential Rules

Represents a collection of sequential rules and their associated quality measure. That is, the elements in the consequent occur at a later time than the elements of the antecedent.

Keywords
classes
##### Note

Some of the methods for sequences are not implemented as objects of this class can be coerced to sequences.

##### Objects from the Class

Typically objects are created by a sequence rule mining algorithm as the result value, e.g. method ruleInduction.

Objects can be created by calls of the form new("sequencerules", ...).

##### Slots

elements:
an object of class itemsets containing a sparse representation of the unique elements of a sequence.
lhs:
an object of class containing a sparse representation of the left-hand sides of the rules (antecedent sequences).
rhs:
an object of class containing a sparse representation of the right-hand sides of the rules (consequent sequences).
ruleInfo:
a data.frame which may contain additional information on a sequence rule.
quality:
a data.frame containing the quality measures of a sequence rule.

##### Extends

Class "associations", directly.

##### Methods

coerce
signature(from = "sequencerules", to = "list")
coerce
signature(from = "sequencerules", to = "data.frame")
coerce
signature(from = "sequencerules", to = "sequences"); coerce a collection of sequence rules to a collection of sequences by appending to each left-hand (antecedent) sequence its right-hand (consequent) sequence.
c
signature(x = "sequencerules")
coverage
signature(x = "sequencerules"); returns the support values of the left-hand side (antecedent) sequences.
duplicated
signature(x = "sequencerules")
labels
signature(x = "sequencerules")
ruleInfo
signature(object = "sequencerules")
ruleInfo<-
signature(object = "sequencerules")
inspect
signature(x = "sequencerules")
is.redundant
signature(x = "sequencerules"); returns a logical vector indicating if a rule has a proper subset in x which has the same right-hand side and the same or a higher confidence.
labels
signature(object = "sequencerules")
length
signature(x = "sequencerules")
lhs
signature(x = "sequencerules")
match
signature(x = "sequencerules")
rhs
signature(x = "sequencerules")
show
signature(object = "sequencerules")
size
signature(x = "sequencerules")
subset
signature(x = "sequencerules")
summary
signature(object = "sequencerules")
unique
signature(x = "sequencerules")

Class , itemsets, associations, , method ruleInduction, is.redundant, function cspade

##### Aliases
• sequencerules-class
• coerce,sequencerules,list-method
• coerce,sequencerules,data.frame-method
• coerce,sequencerules,sequences-method
• generatingItemsets
• coverage,sequencerules-method
• coverage,sequencerules,ANY,missing-method
• is.redundant,sequencerules-method
• summary,sequencerules-method
• show,sequencerules-method
• show,summary.sequencerules-method
• summary.sequencerules-class
• summary,sequencerules-method
##### Examples
## continue example
example(ruleInduction, package = "arulesSequences")
cbind(as(r2, "data.frame"),
coverage = coverage(r2))

## coerce to sequences
as(as(r2, "sequences"), "data.frame")

## find redundant rules
is.redundant(r2, measure = "lift")

Documentation reproduced from package arulesSequences, version 0.2-19, License: GPL-2

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