eclat {arules} | R Documentation |
Mine frequent itemsets with the Eclat algorithm. This algorithm uses simple intersection operations for equivalence class clustering along with bottom-up lattice traversal.
eclat(data, parameter = NULL, control = NULL)
data |
object of class
|
parameter |
object of class
|
control |
object of class
|
Calls the C implementation of the Eclat algorithm by Christian Borgelt for mining frequent itemsets.
Note: Since storing transaction ID lists is very memory intensive, creating transaction ID lists only works for minimum support values which create a small number of itemsets. If memory allocation fails the code currently runs into a segmentation fault.
Returns an object of class itemsets
.
Mohammed J. Zaki, Srinivasan Parthasarathy, Mitsunori Ogihara, and Wei Li. (1997) New algorithms for fast discovery of association rules. Technical Report 651, Computer Science Department, University of Rochester, Rochester, NY 14627.
Christian Borgelt (2003) Efficient Implementations of Apriori and Eclat. Workshop of Frequent Item Set Mining Implementations (FIMI 2003, Melbourne, FL, USA).
ECparameter-class
,
ECcontrol-class
,
transactions-class
,
itemsets-class
,
apriori
data("Adult") ## Mine itemsets with minimum support of 0.1. itemsets <- eclat(Adult, parameter = list(supp = 0.1, maxlen = 15))