sequencerules-class {arulesSequences} | R Documentation |
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.
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", ...)
.
elements
:itemsets
containing a sparse representation of the unique elements of a
sequence.lhs
:sgCMatrix
containing a sparse representation of the left-hand sides of the
rules (antecedent sequences).rhs
:sgCMatrix
containing a sparse representation of the right-hand sides of the
rules (consequent sequences).info
:quality
:
Class "associations"
, directly.
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")
info
signature(object = "sequencerules")
info<-
signature(object = "sequencerules")
inspect
signature(x = "sequencerules")
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")
Some of the methods for sequences are not implemented as objects of this class can be coerced to sequences.
Christian Buchta
Class
sgCMatrix
,
itemsets
,
associations
,
sequences
,
method
ruleInduction
,
function
cspade
## continue example example(ruleInduction, package = "arulesSequences") as(r2, "data.frame") ## coerce to sequences as(as(r2, "sequences"), "data.frame")