基于遗传算法的多决策树融合研究  

Research on Model of Multiple Decision Trees Fusion Based on Genetic Algorithm

作　　者：李广霞[1] 朱峰[2] 张思亮 崔哲[4] 

机构地区：[1]石家庄经济学院信息工程学院,石家庄050031 [2]石家庄职业技术学院实训技术中心,石家庄050081 [3]河北省电视广播大学计算机系,石家庄050071 [4]河北师范大学附属中学信息处,石家庄050016

出　　处：《煤炭技术》2011年第12期130-132,共3页Coal Technology

基　　金：河北省自然科学基金F2008000204

摘　　要：决策树是数据挖掘领域的一种有效方法,但基于决策树挖掘的入侵检测系统存在着检测性能低和数据挖掘效率不高等问题,针对这些问题,该文将遗传算法应用到决策树挖掘策略中。其思想是其思想就是将海量数据集分成若干子数据集,在子数据集上进行挖掘形成不同的子决策树,然后用遗传算法将多棵子决策树进行融合形成最优判断。文章最后通过实验证明该方法的有效性。Decision tree is a highly effective method in data mining. However, the detection performance and the data mining efficiency of data mining-based intrusion detection system is pooper, In order to improve the problem, this paper presents an method based on genetic algorithm. The method based on genetic algorithm is to divide a great large dataset into several sub-datasets. Firstly, detect the network data by different sub-decision trees, and then, genetic algorithm is used to recombine them. So the rule set could be created with the result of the combination. Finally,the results of the experiments indicate that the method is effective.

关 键 词：决策树 数据挖掘 遗传算法 入侵检测 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]