Content deleted Content added
rm ((wikify)) tag - terms in article not already wikified can't be wikified in a practical way |
|||
Line 1:
{{confusing}}
{{cleanup-context}}
'''Apriori''' is an efficient [[association rule]] [[data mining]] algorithm, developed by Rakesh Agrawal, et al..
Apriori employs [[breadth-first search]] and uses a [[hash tree]] structure to count candidate item sets efficiently. The algorithm generates candidate item sets (patterns) of length <math>k</math> from <math>k-1</math> length item sets. Then, the patterns which have an infrequent sub pattern are pruned. According to the [[downward closure lemma]], the generated candidate set contains all frequent <math>k</math> length item sets. Following that, the whole transaction database is scanned to determine frequent item sets among the candidates. For determining frequent items in a fast manner, the algorithm uses a hash tree to store candidate itemsets. Note: This hash tree has item sets at the leaves and [[hash table]]s at internal nodes (Zaki, 99). Note that this is not the same kind of [[hash tree]] structure used in for instance p2p systems.
Apriori is designed to operate on [[database]]s containing transactions (eg: collection of items bought by customers or details of a website frequentation). Other algorithms are designed for finding association rules in data having no transactions (Winepi and Minepi), or having no timestamps (DNA sequencing).
| |||