Knowledge Management System of Hefei Institute of Physical Science，CAS
| 示例学习扩张矩阵的粗糙计算 | |
| 其他题名 | Rough Computation of Extension Matrix for Learning from Examples |
| Hang Xiaoshu1; Xiong Fanlun2; Dai Honghua3 | |
| 2002 | |
| 发表期刊 | 中国科学技术大学学报
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| ISSN | 0253-2778 |
| 摘要 | 为了获得高效率和更简洁的知识，一些启发式算法被提出用于基于扩张矩阵理论的示例学习研究。该文基于粗集理论研究扩张矩阵的示例学习问题，并应用遗传算法获取示例学习中的最优概念。实验结果表明该方法是有效的。提出了粗集理论下的几个新概念，如：必要选择子，核选择子集，约简选择子集和所产生复合的评价指标。 |
| 其他摘要 | To achieve a higher efficient learning rate and to have a simplified representation, extension matrix theory has been applied in several heuristic algorithms for learning practically useful rules from examples. This paper presents a rough set theory based computational approach using the extension matrix theory for learning from examples. The implemented algorithm applied a GA Method to perform optimal learning from given examples. Our experimental results reveal that this approach is potentially useful. Several new concepts including indispensable selector, core set of selectors, reduced set of selectors as well as accuracy, coverage and simplicity for evaluating a complex, are also proposed. |
| 关键词 | 粗糙计算 粗糙集理论 示例学习 扩展距阵 遗传算法 启发式算法 评价指标 |
| 收录类别 | CSCD |
| 语种 | 中文 |
| CSCD记录号 | CSCD:1134242 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.hfcas.ac.cn:8080/handle/334002/97224 |
| 专题 | 中国科学院合肥物质科学研究院 |
| 作者单位 | 1.Department of Automation, USTC 2.Institute of Intelligent Machines, the Chinese Academy of Sciences 3.School of Computing and Mathematics, Deakin University |
| 推荐引用方式 GB/T 7714 | Hang Xiaoshu,Xiong Fanlun,Dai Honghua. 示例学习扩张矩阵的粗糙计算[J]. 中国科学技术大学学报,2002,032. |
| APA | Hang Xiaoshu,Xiong Fanlun,&Dai Honghua.(2002).示例学习扩张矩阵的粗糙计算.中国科学技术大学学报,032. |
| MLA | Hang Xiaoshu,et al."示例学习扩张矩阵的粗糙计算".中国科学技术大学学报 032(2002). |
| 条目包含的文件 | 条目无相关文件。 | |||||
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