摘要
给出了一个基于人工免疫系统的关联规则挖掘算法。将训练数据作为抗原 ,候选模式作为人工识别球 (ARB) ,通过免疫学习生成频繁模式并以免疫记忆的形式加以保存 ,最终生成关联规则。所给的应用实例说明本算法是可行。
In this paper, an algorithm for association rule mining is proposed based on artificial immune system. Training data are regarded as antigens and candidate patterns are regarded as artificial recognition balls. Frequent patterns, from which association rules are generated, are found through the immune learning and stored as the immune memory. A simulated example shows that the algorithm is very effective.
出处
《计算机应用》
CSCD
北大核心
2004年第8期50-53,共4页
journal of Computer Applications
基金
国家自然科学基金项目 (60 0 640 0 2 )
