FP-Growth Algorithm

The FP-Growth algorithm is a method used to find frequent itemsets in large datasets efficiently. Imagine analyzing shopping baskets to see which items are often bought together. Instead of checking every possible combination, FP-Growth builds a compact tree structure called an FP-tree that captures data patterns. It then scans this tree to quickly discover frequently co-occurring items without repeatedly scanning the dataset. This process saves time and resources, making it ideal for market analysis, recommendation systems, and discovering hidden connections in large sets of transactional data.