Frequent itemset mining

Frequent itemset mining is a technique used in data analysis to identify groups of items that often appear together in large datasets, such as shopping baskets or transaction records. For example, it might reveal that people who buy bread also often buy butter. This helps businesses understand patterns and make informed decisions, like product placement or cross-promotions. The process involves scanning data multiple times to find combinations of items that occur frequently enough to be considered significant, highlighting valuable relationships within the data.