计算机工程与科学2012，Vol.34Issue(3)：118-121,4.DOI:10.3969/j.issn.1007-130X.2012.03.022
基于免疫克隆文化算法的关联规则挖掘
Mining Association Rules Based on Immune Clone Culture Algorithm
杨光军1
作者信息
- 1. 德州学院机电工程系,山东德州253023
- 折叠
摘要
Abstract
Association rules mining is an important problem in data mining. The traditional mining algorithms have high complexity and low efficiency, while the intelligent algorithms have the advantages of maintenance of population diversity and robustness in the searching process. A model of mining association rules based on immune clone culture algorithm is proposed. This model takes advantages of global searching in the immune clone algorithm to rapidly search the frequent item sets and then extract the interesting rules. It also uses the knowledge structure of belief space in the culture algorithm to guide the population's evolution and enhance the purpose and directivity of searching. The experiments show that the new model has faster performance speed and also improves the accuracy of the rules.关键词
关联规则/免疫克隆算法/文化算法Key words
association rules/immune clone algorithm/culture algorithm分类
信息技术与安全科学引用本文复制引用
杨光军..基于免疫克隆文化算法的关联规则挖掘[J].计算机工程与科学,2012,34(3):118-121,4.
