International Journal of Computer Science and Mobile Computing (IJCSMC)
Association rule mining plays an important role in field of data mining because amount of data is increasing daily and mining the important and relevant information from this huge amount of data is a tedious task. In field of data mining, mining the frequent itemsets from huge amount of data stored in database is an important task. Frequent itemsets leads to formation of association rules. Various methods have been proposed and implemented to improve the efficiency of Apriori algorithm. This paper focuses on comparing the improvements proposed in classical Apriori algorithm for frequent item set mining.