Abstract
Apriori algorithm is a data mining method which finds all frequent itemsets and association rules in given data. An association rule has the form \(X \rightarrow Y\), where X and Y are itemsets, and the interpretation is that if set X occurs in an example, then set Y is also likely to occur in the example. The algorithm first finds frequent itemsets by a breadth-first, general-to-specific search. It then generates association rules from the itemsets.
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References
Agrawal R, Mannila H, Srikant R, Toivonen H, Verkamo AI (1996) Fast discovery of association rules. In: Fayyad UM, Piatetsky-Shapiro G, Smyth P, Uthurusamy R (eds) Advances in knowledge discovery and data mining. AAAI Press, Menlo Park, pp 307–328
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Toivonen, H. (2023). Apriori Algorithm. In: Phung, D., Webb, G.I., Sammut, C. (eds) Encyclopedia of Machine Learning and Data Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7502-7_10-1
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DOI: https://doi.org/10.1007/978-1-4899-7502-7_10-1
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