AnalyzeMarket Basket Data using FP-growth and Apriori Algorithm
Data mining is the process of analyzing or extracting large amount of data from different perspectives and summarizing it into useful information. In this paper the authors find the association rules among the large dataset. To find association rules they use two algorithms i.e. FP-growth and apriori algorithms. First they find frequent itemsets using weka tool and rapid-miner tool. Then they generate association rules from the frequent itemsets. They have analyzed that as per this research FP-tree much faster than apriori algorithm to generate association rules when they use large dataset.