| C4.5决策树改进算法研究 |
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| 引用本文： | 冯帆,徐俊刚.C4.5决策树改进算法研究[J].电子技术,2012,39(6):1-4. |
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| 作者姓名： | 冯帆 徐俊刚 |
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| 作者单位： | 中国科学院研究生院 |
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| 摘 要： | 决策树是数据挖掘分类算法中非常重要的一个算法分支。文章介绍了决策树算法中应用最广泛的典型算法-ID3和C4.5算法,并基于四个通用的数据集,针对这两个算法进行定量分析对比,研究两个算法的性能优劣。文章对C4.5算法中的连续属性离散化方法提出一些优化改进,并通过实际数据实验证实了优化的可行性。
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| 关 键 词： | 数据挖掘 分类算法 决策树 ID3算法 C4.5算法 离散化 边界原理 |
Research on Decision Tree Algorithm & Its Application in CRM System |
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| Feng Fan
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Xu Jungang.Research on Decision Tree Algorithm & Its Application in CRM System[J].Electronic Technology,2012,39(6):1-4. |
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| Authors: | Feng Fan Xu Jungang |
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| Affiliation: | Feng Fan Xu Jungang(Graduate University of Chinese Academy of Sciences) |
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| Abstract: | The Decision Tree Algorithm is a very important branch of the Classify Algorithms in Data Mining.This article introduces two typical Decision Tree Algorithms-ID3 and C4.5.It also quantitatively compares and analyzes ID3 with C4.5 based on 4 general data sets,summarizing the advantages and disadvantages of two algorithms.This article also proposes an improvement for the discretization method of the numeric attributes values in C4.5 algorithm and verifies the feasibility of the optimization through practical data experiment. |
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| Keywords: | data mining classification algorithm decision tree ID3 algorithm C4 5 algorithm Discretization boundary theory |
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