Apriori is an algorithm for frequent item set mining and association rule learning over transactional 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.
| Category | Usage | Application Field |
|---|---|---|
| Unsupervised Learning | Association Rule Learning | Frequent Itemset Mining |
Use apriori principle to reduse the size of candidate set