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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
【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。
【Abstract】 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.
【Key words】 decision tree; data mining; genetic algorithm; intrusion detection;
- 【文献出处】 煤炭技术 ,Coal Technology , 编辑部邮箱 ,2011年12期
- 【分类号】TP311.13;TP18
- 【被引频次】4
- 【下载频次】137