| HGR 2.0： A New Rule Induction Algorithm |
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| 引用本文： | 谌卫军,Lin Fuzong,Li Jianmin,Zhang Bo.HGR 2.0： A New Rule Induction Algorithm[J].高技术通讯(英文版),2003,9(3):24-28. |
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| 作者姓名： | 谌卫军 Lin Fuzong Li Jianmin Zhang Bo |
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| 作者单位： | DepartmentofComputerSdeiaeeandTechnology,TsinghuaUniversity,Beijing100084,P.R.China) |
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| 基金项目： | theNationalNaturalScienceFoundationofChina . |
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| 摘 要： | This paper presents a new inductive learning algorithm, HGR (Version 2.0), based on the newly-developed extension matrix theory The basic idea is to partition the positive examples of a specific class in a given example set into consistent groups, and each group corresponds to a consistent rule which covers all the examples in this group and none of the negative examples. Then a performance comparison of the HGR algorithm with other inductive algorithms, such as C4.5,OC1, HCV and SVM, is given in the paper. The authors not only selected 15 databases from the famous UCI machine learning repository, but also considered a real world problem. Experimental results show that their method achieves higher accuracy and fewer rules as compared with other algorithms.
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| 关 键 词： | 规则归纳学习算法 HGR2.0 机器学习 扩展矩阵理论 人工智能 |
HGR 2.0: A New Rule Induction Algorithm |
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| Lin Fuzong,Li Jianmin,Zhang Bo.HGR 2.0: A New Rule Induction Algorithm[J].High Technology Letters,2003,9(3):24-28. |
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| Authors: | Lin Fuzong Li Jianmin Zhang Bo |
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| Abstract: | This paper presents a new inductive learning algorithm, HGR (Version 2.0), based on the newly-developed extension matrix theory. The basic idea is to partition the positive examples of a specific class in a given example set into consistent groups, and each group corresponds to a consistent rule which covers all the examples in this group and none of the negative examples. Then a performance comparison of the HGR algorithm with other inductive algorithms, such as C4.5, OC1, HCV and SVM, is given in the paper. The authors not only selected 15 databases from the famous UCI machine learning repository, but also considered a real world problem. Experimental results show that their method achieves higher accuracy and fewer rules as compared with other algorithms. |
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| Keywords: | inductive learning algorithm machine learning extension matrix theory |
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