The Apriori algorithm is particularly designed for mining frequent item-sets and generating association rules which could be of interest
- Proposed by Rakesh Agrawal and Ramakrishnan Srikant in 1994
- The algorithm works by iteratively discovering frequent item-sets in a dataset and then generating association rules based on those frequent item-sets
- The frequent item-set is determined by comparing the determined frequency of each item and item-set with the provided support value
Frequent item-set
A frequent item-set is a set of items that frequently appear together in the dataset. The algorithm uses a level-wise search strategy to discover these frequent item-sets and then derives association rules based on these frequent item-sets.