基于抗体浓度和亲合度的关联规则挖掘算法

Association rule algorithm based on concentration and affinity of antibodies

关联规则是数据挖掘的重要模式之一,有着极其重要的应用价值。基于抗体浓度和亲合度的选择策略,提出了一种克隆模拟退火遗传挖掘算法。该挖掘算法先通过克隆操作来产生一组新的抗体,然后再独立地对所产生的抗体进行变异和克隆选择操作,从而求得问题的最优解。实验结果表明该算法能高效地解决关联规则挖掘问题。

Association rule is one of the important models of data mining,and has the most significant application value.This paper combining with the concentration and affinity of antibodies,brings forward a method of mining association rules based on clonal simulated annealing genetic algorithm.It first generates a new group of individuals through elonal operation,and makes mutation/selection independently with all the generated individuals respectively.Experiment results demonstrate that this method can solve association rule mining effectively.