摘要
针对传统ID3算法计算过程复杂以及存在信息冗余的问题,提出了一种改进算法——基于粗糙集属性约简的简化ID3算法.该算法利用粗糙集中属性约简的性质删掉了系统中多余的知识,在保证同样的分类能力下使得分类系统更简洁,同时借助了泰勒公式对熵公式进行化简,使得计算更简便,然后把改进的算法用到实例中去,并用相关数据库上的大量数据编程进行仿真实验,最后得出的仿真结果证明了所提出算法的正确性与可行性,不仅能够有效降低信息重复度,减少了冗余规则,还保证了算法精度,同时为把ID3算法更好地应用到现实生活实例中提供了一定的参考价值.
Aiming at solving the problem that the traditional ID3 algorithm is complicated and there exists redundancy information, this study proposes an improved algorithm attribute reduct simplified ID3 algorithm based on rough set. This algorithm uses the properties of attribute reduct in rough set to delete the redundant knowledge, and makes the classification system more concise with the same classification ability. At the same time, it simplifies the entropy formula with Taylor formula to make the calculation easier. And then this study applies the improved algorithm to the example, and uses the massive data in the related database to program in order to do simulation experiments. Finally, the simulation results proved the correctness and feasibility of the proposed algorithm. It can not only reduce the information duplication, reduce the redundancy rules, but also ensure the accuracy of the algorithm. At the same time, it provides a certain reference value for the better application of ID3 algorithm to real life examples.
作者
余建军
张琼之
YU Jian-Jun;ZHANG Qiong-Zhi(School of Business Administration,South China University of Technology,Guangzhou 510640,China)
出处
《计算机系统应用》
2020年第4期156-162,共7页
Computer Systems & Applications
基金
广东省哲学社会科学“十三五”规划学科共建项目(GD17XGL56)。
关键词
决策树
ID3算法
粗糙集
属性约简
仿真
decision tree
ID3 algorithm
rough set
attribute reduct
simulation
