一种改进的决策树ID3算法的应用
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摘要
决策树ID3算法是经典的数据挖掘分类算法,从引入专业领域的经验值、简化属性增益值的运算量、设置剪枝阈值这三个方面对算法进行改进。选取部分大学生足球运动训练样本集,参考体育专家根据经验给出的属性权重,快速且合理地形成决策树,相比与原ID3算法分类结果一致,但效率得到明显提高。
Decision tree ID3 algorithm is a classical data mining classification algorithm. Improves the algorithm from three aspects: introducing experience value in professional field, simplifying the calculation amount of attribute gain value and setting pruning threshold. Selecting some sample sets of College Students' football training, referring to the attribute weights given by sports experts according to experience, the decision tree can be formed quickly and reasonably. Compared with the original ID3 algorithm, the classification result is consistent, but the efficiency is improved obviously.
Decision tree ID3 algorithm is a classical data mining classification algorithm. Improves the algorithm from three aspects: introducing experience value in professional field, simplifying the calculation amount of attribute gain value and setting pruning threshold. Selecting some sample sets of College Students' football training, referring to the attribute weights given by sports experts according to experience, the decision tree can be formed quickly and reasonably. Compared with the original ID3 algorithm, the classification result is consistent, but the efficiency is improved obviously.
引文
[1]范明,孟小峰,译.数据挖掘概念与技术,机械工业出版社,2001.
[2]Quinlan J R. Induction of Decision Trees[J]. Machine Learning,1986:257-264.
[3]史忠植.知识发现[M].北京:清华大学出版社,2002.
[4]滕皓,赵国毅.改进决策树的研究[J].济南大学学报:自然科学版,2002,16(3):231-233.
[5]王静红,王熙照,邵艳华,等.决策树算法的研究及优化[J].微机发展,2004,14(9):30-32.
[6]王熙照,谢竞博.基于属性间交互信息的模糊ID3算法的扩展[J].复旦学报(自然科学版),2004,43(5):777-780.
[7]丁华,张少中,王秀坤.基于改进ID3算法的轨迹化决策研究[J].计算机工程与设计,2004,25(10):1721-1723.
[8]魏涛.改进的ID3算法及其在教育信息挖掘中的应用[J].上海海事大学学报,2005,26(3):82-84.
[9]王艳兵,赵锐,姚青.基于可变精度的ID3改进算法[J].计算机工程与设计,2006,27(14):2683-2685.
[10]刘莘,张永平,万艳丽.决策树算法在入侵检测中的应用分析及改进[J].计算机工程与设计,2006,27(19):3641-3643.
[11]刘小虎,李生.决策树的优化算法[J].软件学报,1998,9(10):798-801.
[12]郭玉滨.决策树ID3算法研究及其改进[J].菏泽学院学报,2005,27(5):44-46.
[13]陈文伟.数据仓库与数据挖掘教程.清华大学出版社,2006-8.
[14]段玉春,朱晓艳,孙玉强.一种改进ID3算法[J].南阳师范学院学报,2006,5(9):64-65.
[2]Quinlan J R. Induction of Decision Trees[J]. Machine Learning,1986:257-264.
[3]史忠植.知识发现[M].北京:清华大学出版社,2002.
[4]滕皓,赵国毅.改进决策树的研究[J].济南大学学报:自然科学版,2002,16(3):231-233.
[5]王静红,王熙照,邵艳华,等.决策树算法的研究及优化[J].微机发展,2004,14(9):30-32.
[6]王熙照,谢竞博.基于属性间交互信息的模糊ID3算法的扩展[J].复旦学报(自然科学版),2004,43(5):777-780.
[7]丁华,张少中,王秀坤.基于改进ID3算法的轨迹化决策研究[J].计算机工程与设计,2004,25(10):1721-1723.
[8]魏涛.改进的ID3算法及其在教育信息挖掘中的应用[J].上海海事大学学报,2005,26(3):82-84.
[9]王艳兵,赵锐,姚青.基于可变精度的ID3改进算法[J].计算机工程与设计,2006,27(14):2683-2685.
[10]刘莘,张永平,万艳丽.决策树算法在入侵检测中的应用分析及改进[J].计算机工程与设计,2006,27(19):3641-3643.
[11]刘小虎,李生.决策树的优化算法[J].软件学报,1998,9(10):798-801.
[12]郭玉滨.决策树ID3算法研究及其改进[J].菏泽学院学报,2005,27(5):44-46.
[13]陈文伟.数据仓库与数据挖掘教程.清华大学出版社,2006-8.
[14]段玉春,朱晓艳,孙玉强.一种改进ID3算法[J].南阳师范学院学报,2006,5(9):64-65.