A New Approach to Find Predictor of Software Fault Using Association Rule Mining

These data are analyzed using Association rule to find the interestingness of student in opting class teaching language.. In order to apply this following steps are performed

Association rule hiding is one of the techniques of privacy preserving data mining to protect the sensitive association rules generated by association rule mining.. This paper

This problem used to mine frequent patterns from the databases like Retail transaction database, Chess database and Mushroom database using association mining

All association rule mining algorithms like apriori algorithm and fp-growth algorithms are using mainly two steps in extracting the association rule. 1) Generation of

Thus the main aim of this research is to perform association rule from multiple heterogeneous data sources using multi agent system and then unifying the result to knowledge base

After studying the algorithm on Association Rule Mining using the APRIORI technique, it has been analyzed that this technique is useful for only small datasets ,on

Our research is a further step of the Tree Based Association Rule Mining (TBAR) algorithm, used in relational databases for finding the association rules .In

In this paper we propose a new approach based on Particle Swarm Optimization Algorithm to mine association rules for both frequent and infrequent itemsets in an efficient way.