| 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.
coercesignature(from = "sequencerules", to = "list")coercesignature(from = "sequencerules", to = "data.frame")coercesignature(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.csignature(x = "sequencerules")coveragesignature(x = "sequencerules");
returns the support values of the left-hand side (antecedent)
sequences.duplicatedsignature(x = "sequencerules")labelssignature(x = "sequencerules")infosignature(object = "sequencerules")info<-signature(object = "sequencerules")inspectsignature(x = "sequencerules")labelssignature(object = "sequencerules")lengthsignature(x = "sequencerules")lhssignature(x = "sequencerules")matchsignature(x = "sequencerules")rhssignature(x = "sequencerules")showsignature(object = "sequencerules")sizesignature(x = "sequencerules")subsetsignature(x = "sequencerules")summarysignature(object = "sequencerules")uniquesignature(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")