FPGrowth Algorithm

FPGrowth is an algorithm used in data analysis to find frequent patterns or groups within large datasets efficiently. It works by building a compact structure called an FP-tree that summarizes all transactions, highlighting common item combinations. This tree allows the algorithm to quickly identify which items often appear together without repeatedly scanning the entire data. By doing so, FPGrowth can discover associations, such as products frequently bought together, helping with market basket analysis and decision-making. Its efficiency comes from reducing redundant processing and focusing on relevant patterns within the data.