
transactions
object using different
methods.random.transactions(nItems, nTrans, method = "independent", ...,
verbose = FALSE)
transactions
.nitems
times ntrans
transaction database.
Currently two simulation methods are implemented:
[object Object],[object Object]Rakesh Agrawal and Ramakrishnan Srikant (1994). Fast algorithms for mining association rules in large databases. In Jorge B. Bocca, Matthias Jarke, and Carlo Zaniolo, editors, Proceedings of the 20th International Conference on Very Large Data Bases, VLDB, pages 487--499, Santiago, Chile.
transactions-class
.## generate random 1000 transactions for 200 items with
## a success probability decreasing from 0.2 to 0.0001
## using the method described in Hahsler et al. (2006).
trans <- random.transactions(nItems = 200, nTrans = 1000,
iProb = seq(0.2,0.0001, length=200))
## display random data set
image(trans)
## use the method by Agrawal and Srikant (1994) to simulate transactions
## which contains correlated items. This should create data similar to
## T10I4D100K (just only 1000 transactions)
patterns <- random.patterns(nItems = 1000)
summary(patterns)
trans2 <- random.transactions(nItems = 1000, nTrans = 1000,
method = "agrawal", patterns = patterns)
image(trans2)
## plot data with items ordered by item frequency
image(trans2[,order(itemFrequency(trans2), decreasing=TRUE)])
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