Datamining 9th Association Rule

The document describes the Apriori algorithm for frequent itemset mining and association rule learning over transactional data. Apriori uses a bottom-up approach where frequent subsets are extended one item at a time, and groups of candidates are tested against the data. The algorithm performs multiple passes over the data and prunes itemsets whose subsets are infrequent. This process counts transaction IDs where itemsets occur and allows mining associations between items in large datasets.