基于混合遗传克隆算法的关联规则挖掘

针对在数据挖掘应用中关联规则挖掘的问题,给出一种基于混合遗传克隆算法的关联规则挖掘方法,该算法将遗传算法和克隆算法优点相结合,通过克隆操作来产生一组新的个体,独立地对所产生的各个体进行变异,交叉操作,同时采用自适应方式动态选取交叉和变异概率,有效地克服了遗传算法容易陷入局部最优的缺点,从而求得问题的最优解。实验结果表明,该方法能高效地解决关联规则挖掘问题。

Association Rule Mining Based on Hybrid Genetic Clonal Algorithm

Aiming at the problem of association rules mining in the application of data mining, this paper proposes a method of mining association rules based on Hybrid Genetic Clonal Algorithm(HGCA). This algorithm combines with the Clonal Algorithm(CA) and Genetic Algorithm(GA) to fully exert respective advantages. It generates a new group of individuals through clonal operation, makes mutation and crossover independently all the generated individuals respectively, uses adaptive crossover probability and mutation probability so as to restrain premature convergence. Experimental results demonstrate that this method can solve association rule mining effectively.