apriori {arules} | R Documentation

## Mining Associations with Apriori

### Description

Mine frequent itemsets, association rules or association hyperedges using the Apriori algorithm. The Apriori algorithm employs level-wise search for frequent itemsets. The implementation of Apriori used includes some improvements (e.g., a prefix tree and item sorting).

### Usage

    apriori(data, parameter = NULL, appearance = NULL, control = NULL)

### Arguments

`data` | object of class `transactions` or any data structure which can be coerced into `transactions` (e.g., a binary matrix or data.frame).
`parameter` | object of class `APparameter` or named list. The default behavior is to mine rules with support 0.1, confidence 0.8, and maxlen 5.
`appearance` | object of class `APappearance` or named list. With this argument item appearance can be restricted. By default all items can appear unrestricted.
`control` | object of class `APcontrol` or named list. Controls the performance of the mining algorithm (item sorting, etc.)

### Details

Calls the C implementation of the Apriori algorithm by Christian Borgelt for mining frequent itemsets, rules or hyperedges.

### Value

Returns an object of class `rules` or `itemsets`.

### References

R. Agrawal, T. Imielinski, and A. Swami (1993) Mining association rules between sets of items in large databases. In Proceedings of the ACM SIGMOD International Conference on Management of Data, pages 207–216, Washington D.C.

Christian Borgelt and Rudolf Kruse (2002) Induction of Association Rules: Apriori Implementation. 15th Conference on Computational Statistics (COMPSTAT 2002, Berlin, Germany) Physica Verlag, Heidelberg, Germany.

Christian Borgelt (2003) Efficient Implementations of Apriori and Eclat. Workshop of Frequent Item Set Mining Implementations (FIMI 2003, Melbourne, FL, USA).

### See Also

`APparameter-class`, `APcontrol-class`, `APappearance-class`, `transactions-class`, `itemsets-class`, `rules-class`

### Examples

    data("Adult")
    ## Mine association rules.
    rules <- apriori(Adult,
                     parameter = list(supp = 0.5, conf = 0.9,
                                      target = "rules"))
    summary(rules)

[Package arules version 0.6-3 Index]