Application of a New Association Rules Mining Algorithm in the Chinese Medical Coronary Disease
作者： Feng Yuan , Hong Liu , ShouQiang Chen
DOI: 10.1007/978-94-007-7618-0_36
关键词: Coronary disease 、 Genetic algorithm 、 Fitness function 、 Data mining 、 Association (object-oriented programming) 、 Data mining algorithm 、 Population 、 Particle swarm optimization 、 Association rule learning 、 Computer science
摘要: The paper deals with efficient mining association rules in large data sets of TCM clinical the coronary disease. Aiming at problems that exist a great deal and high characteristics, which lead to problem low efficiency, slow convergence omission rules, new combined method is proposed based on genetic algorithm particle swarm optimization. designs fitness function, uses optimization finish evolution integration, combines manipulation advantage simple robust. medical treatment records disease were verified by experiments. Experimental results show compared traditional method, performs better terms diversity population discovering more effective rules. result has reference value
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