Mining Efficient Association Rules Through Apriori Algorithm Using Attributes and Comparative Analysis of Various Association Rule Algorithms
In frequent pattern mining, there are several algorithms. Apriori is the classical and most famous algorithm. Objective of using Apriori algorithm is to find frequent itemsets and association between different itemsets i.e. association rule. In this paper, authors consider data (bank data) and try to obtain the result using weka a data mining tool. Association rule algorithms are used to find out the best combination of different attributes in any data. In this paper author uses apriori to find association rule. Here author consider three association rule algorithms: apriori association rule, predictive apriori association rule and tertius association rule.