摘要
针对ID3算法倾向于选择取值较多的属性的缺点,引进属性重要性来改进ID3算法,并根据改进的ID3算法中信息增益的计算特点,利用凸函数的性质来简化该算法.实验表明,优化的ID3算法与原ID3算法相比,在构造决策树时具有较高的准确率和更快的计算速度,并且构造的决策树还具有较少的平均叶子数.
For the shortcoming that ID3 algorithm tends to choose attribute which has many values,attribute importance was introduced to improve ID3 algorithm.Next,according to the character of information gain,the improved ID3 algorithm was simplified to reduce the complexity of computing information gain by the convex function.Through experiment testing,the optimized ID3 algorithm can spend much less time to construct the high accurate decision tree and this decision tree has less average leaves.
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
2010年第7期883-886,891,共5页
Journal of Shanghai Jiaotong University
基金
四川省科技计划项目(2008GZ0003)
四川省科技厅科技攻关项目(07GG006-019)
关键词
决策树
ID3算法
属性重要性
信息增益
凸函数
decision tree
ID3 algorithm
attribute importance
information gain
convex function