Apriori algorithm: Difference between revisions

Revision as of 15:38, 15 March 2019

Revision as of 11:04, 22 September 2019

Line 1:

{{Refimprove|date=September 2018}}

'''Apriori'''<ref name=apriori>Rakesh Agrawal and Ramakrishnan Srikant [http://www.vldb.org/conf/1994/P487.PDF Fast algorithms for mining association rules]. Proceedings of the 20th International Conference on Very Large Data Bases, VLDB, pages 487-499, Santiago, Chile, September 1994.</ref> is an [[algorithm]] for frequent item set mining and [[association rule learning]] over transactionalrelational [[databases]]. It proceeds by identifying the frequent individual items in the database and extending them to larger and larger item sets as long as those item sets appear sufficiently often in the database. The frequent item sets determined by Apriori can be used to determine [[association rules]] which highlight general trends in the [[database]]: this has applications in domains such as [[market basket analysis]].

== Overview ==