An Improved Apriori Algorithm and its Application in TCM Treatment of Coronary Heart Disease

摘要

Against the drawbacks of the Apriori algorithm, this paper proposes an improved Apriori algorithm. When pruning the candidate itemsets, this algorithm adopts a new method to reduce the redundant generation of sub-itemsets, which can generate frequent itemsets and delete candidates having a subset that is infrequent simultaneously. The improved algorithm greatly raises the efficiency of frequent itemsets generation with the run time less than one-tenth of the of original algorithm, and saves lots of storage space. In the end, the original algorithm and the improved algorithm are used to mine association rules in the data of TCM(Traditiona! Chinese Medicine) treatment of coronary heart disease, and the experimental results demonstrate the latter's effectiveness and efficiency.