A Novel Approach for Data Mining Clustering Technique Using NeuralGas Algorithm

Efficient Privacy preserving association rule mining has emerged as a latest research issue. In this thesis work, existing algorithms, Increase Support of Left and Decrease Support of Right are implemented successfully on the real data for Privacy Preserving Association Rule Mining. In order to hide an association rule, a hybrid algorithm is proposed which is based on two previous existing algorithms ISL and DSR. K-Mean, Neural gas Cluster Algorithm with Number of cluster in this algorithm, first we decrease support of right hand side of the rule in a rule where item to be hide is in right side for Experimental work, we have used a real time database of Doctor Patient Evaluation from Medical College.