| 基于粗集理论的新决策树剪枝方法 |
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| 引用本文： | 王名扬,卫金茂,伊卫国.基于粗集理论的新决策树剪枝方法[J].东北师大学报(自然科学版),2005,37(3):28-32. |
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| 作者姓名： | 王名扬 卫金茂 伊卫国 |
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| 作者单位： | 东北师范大学物理学院,吉林,长春,130024;东北师范大学物理学院,吉林,长春,130024;东北师范大学物理学院,吉林,长春,130024 |
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| 基金项目： | 吉林省科技发展计划，东北师范大学校科研和教改项目 |
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| 摘 要： | 提出了一种基于粗糙集理论的新决策树剪枝方法.在剪枝的过程中,不仅考虑了树的分类精度,而且还考虑了生成树的深度对剪枝的影响;最后针对具体的数据集对新方法进行了验证,得到了较好的效果.
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| 关 键 词： | 过匹配 剪枝 深度拟合率 错误率 |
| 文章编号： | 1000-1832(2005)03-0028-05 |
| 收稿时间： | 12 30 2004 12:00AM |
| 修稿时间： | 2004年12月30 |
A new decision tree pruning method based on RST |
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| WANG Ming-yang,WEI Jin-mao,YI Wei-guo.A new decision tree pruning method based on RST[J].Journal of Northeast Normal University (Natural Science Edition),2005,37(3):28-32. |
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| Authors: | WANG Ming-yang WEI Jin-mao YI Wei-guo |
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| Abstract: | Pruning decision tree is an effective way to avoid the phenomena of overfitting.This paper gives a new decision tree pruning method based on Rough Set Theory(RST),which holds that the complexity of the decision tree should also be regarded besides the classification accuracy of the tree in the process of pruning decision tree.It takes into account not only the classification accuracy of the tree but also the depth of the tree.Finally,a data set is given to validate the new method which has shown good performance. |
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| Keywords: | overfitting pruning depth - fitting ratio error ratio |
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