Analyzing Transaction database using Fast Online Dynamic-Growth (FOLD-growth) algorithm

Abstract

Data mining is the process of analyzing large data sets in order to find patterns. Mining frequent patterns is a fundamental and crucial task in data mining problems. The association rule mining is needed in order to search for interesting relationship among items from a very large database. FP-Growth algorithm that allows mining of the frequent itemsets without candidate generation. In this paper, implement the pattern growth approach (FOLD-Growth) algorithm is used to analyze transaction database in the real world.