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基于相似度的交叉变异算子及其在分类规则挖掘中的应用
Similarity-based crossover-mutation operator and its application to mining classification rules
【摘要】 在简单遗传算法基础上,引入“相似度”和“杂交优势”思想,将原来的交叉和变异两个算子合二为一,提出了一个新的遗传算子:基于相似度的交叉变异算子。将算子应用于分类规则的挖掘中,既可提高算法的收敛速度,又能抑制早熟收敛现象的发生。
【Abstract】 Based on the simple genetic algorithm the idea of "similarity degree" and "beneficial crossover" is introduced and a new operator called similarity-based crossover-mutation is presented by combining the crossover with the mutation.Applying new operator to mining classification rules it is found to speed up the algorithm convergence and restrain the premature convergence to some extent.
【关键词】 数据挖掘;
遗传算法;
相似度;
交叉变异算子;
分类规则;
【Key words】 data mining; genetic algorithm; similarity degree; crossover-mutation operato4r; classification rule;
【Key words】 data mining; genetic algorithm; similarity degree; crossover-mutation operato4r; classification rule;
- 【文献出处】 成都信息工程学院学报 ,Journal of Chengdu University of Information Technology , 编辑部邮箱 ,2007年01期
- 【分类号】TP311.13
- 【被引频次】5
- 【下载频次】113