arulesSequences (version 0.1-3)

cspade: Mining Associations with cSPADE

Description

Mining frequent sequential patterns with the cSPADE algorithm. This algorithm utilizes temporal joins along with efficient lattice search techniques and provides for timing constraints.

Usage

cspade(data, parameter = NULL, control = NULL)

Arguments

data

an object of class transactions with temporal information.

parameter

an object of class SPparameter.

control

an object of class SPcontrol.

Value

• Returns an object of class sequences.

Details

Interfaces the command-line tools for preprocessing and mining frequent sequences with the cSPADE algorithm by M. Zaki via a proper chain of system calls.

The temporal information is taken from components sequenceID (sequence or customer identifier) and eventID (event identifier) of slot transactionInfo. The utility function read_baskets provides for reading of text files with temporal transaction data.

References

M. J. Zaki. (2001). SPADE: An Efficient Algorithm for Mining Frequent Sequences. Machine Learning Journal, 42, 31--60.

See Also

Class transactions, sequences, SPparameter, SPcontrol, method ruleInduction, function read_baskets.

Examples

## use example data from paper
data(zaki)
## mine frequent sequences
s1 <- cspade(zaki, parameter = list(support = 0.4), 
		   control   = list(verbose = TRUE))
summary(s1)
as(s1, "data.frame")
## use timing constraint
s2 <- cspade(zaki, parameter = list(support = 0.4, maxwin = 5))
as(s2, "data.frame")