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Keywords: APriori algorithm , Association rules , Data mining , item based partitioning , multi Dimensional analysis.

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Data mining techniques have led over various methods to gain knowledge from vast amount of data. So different research tools and techniques like classification algorithm, decision tree, association rules etc are available for bulk amount of data. Association rules are mainly used in mining transaction data to find interesting relationship between attribute values and also it is a main topic of data mining There is a a great challenge in candidate generation for large data with low support threshold. Through this paper we are making a study to show how association rules will be effective with the dense data and low support threshold. The data set which we have used in this paper is real time data of certain area and we are applying the data set in association rules to predict the chance of disease hit in that area using A Priori Algorithm. In this paper three different sets of rules are generated with the dataset and applied the apriori algorithm with it. With the algorithm, found the relation between the parameters in the database.


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