The Research And Application Of Data Mining In Insurance

Data Mining is a newer database technique which aims at discovering potential and valuable pattern that is called as knowledge.The knowledge discovered can be used for decision-making. Data Mining is widely needed in practical field, therefor; either the theorical research or the practice of Data Mining is significative.Mining for association rules is an important embranchment of Data Mining. Some successful algorithms have been discovered in this field. The main subject is to find interesting association or correlation relationships among a large set of data items. Finding all frequent itemsets is the first step of association rule mining. The main method of realization usually used is algorithm like Apriori to find frequent itemsets. But, efficiency of the Apriori algorithm needs to be improved.In some huge databases the cost of finding all frequent itemsets is vast. In this paper, I analyses and realizes an improved association rule algorithm, the algorithm FMFI. FMFI is backtrack search based algorithm for mining maximal frequent itemsets. It uses a techniquecalled progressive focusing to perform maximality checking, and diffset propagation to perform fast frequency computation.So, It can fast prune the search space.In this paper, We discuss the use of data mining in Insurance enterprise.and give an example how to design a data mining system, and using it to predict with a model.