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")

See Also

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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