ruleInduction-methods: Induce Sequence Rules

In arulesSequences: Mining Frequent Sequences

Induce Sequence Rules

Description

Induce a set of strong sequence rules from a set of frequent sequences, i.e. which (1) satisfy the minimum confidence threshold and (2) which contain the last element of the generating sequence as the right-hand side (consequent) sequence.

Usage

## S4 method for signature 'sequences'
ruleInduction(x, transactions, confidence = 0.8, control = NULL)

Arguments

x	an object.
transactions	an optional object of class transactions with temporal information.
confidence	a numeric value specifying the minimum confidence threshold.
control	a named list with logical component verbose specifying if progress and runtime information should be displayed.

Details

If transactions is not specified, the collection of sequences supplied must be closed with respect to the rules to be induced. That is, the left- and the right-hand side sequence of each candidate rule must be contained in the collection of sequences. However, using timing constraints in the mining step the set of frequent sequences may not be closed under rule induction.

Otherwise, x is completed (augmented) to be closed under rule induction and the support is computed from transactions, using method ptree. Note that, rules for added sequences, if any, are not induced.

Value

Returns an object of class sequencerules.

Author(s)

Christian Buchta

See Also

Class sequences, sequencerules, method support, function cspade.

Examples

## continue example
example(cspade)

## mine rules
r2 <- ruleInduction(s2, confidence = 0.5,
			control    = list(verbose = TRUE))
summary(r2)
as(r2, "data.frame")

arulesSequences documentation built on Sept. 11, 2024, 9:35 p.m.