摘要
蚁群算法是一种新型的用于求解组合优化或函数优化问题的启发式算法,其基本思想是借用生物界的蚂蚁群体觅食机理,将每个蚂蚁看作一个智能体.本文提出一种基于蚁群系统的数据挖掘中的关联规则挖掘模式。这种基于启发式优化算法的模式可以为用户决策提供一个很好的支持。这种方式可以很快的找到关联规则也可以确保规则结果的准确性。最后用实验结果的对比来进一步说明这种方法的高效和准确性。
Ant colony algorithm is a new kind of meta-heuristic algorithms for solving combinatorial optimization problems or continuous function optimization problems,and it borrows the mechanism of ant search,and every ant is looked for as all agent.This paper presents an ant colony system-based data mining,association rule mining model.This heuristic algorithm based on user decision-making model can provide a good support.This way you can quickly find the association rules to ensure the accuracy of the results of the rules.Finally,we use the experimental results to further illustrate the method efficiency and accuracy.
出处
《软件》
2012年第10期16-19,共4页
Software
基金
中央高校基本科研项目
北京邮电大学青年科研创新计划专项(编号:2012RC0201)
关键词
机器学习
蚁群算法
启发式
关联规则
数据挖掘
Machine Learning
Ant colony algorithm
heuristic
association rule
data mining
