| 一种高效的基于联合熵的边界点检测算法 |
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| 引用本文： | 邱保志,曹鹤玲.一种高效的基于联合熵的边界点检测算法[J].控制与决策,2011,26(1):71-74. |
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| 作者姓名： | 邱保志 曹鹤玲 |
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| 作者单位： | 郑州大学,信息工程学院,郑州,450001 |
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| 基金项目： | 周家自然科学墓金项目，河南省教育厅自然科学基金项目 |
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| 摘 要： | 为了快速有效地检测出聚类的边界点,提出一种将网格技术与联合熵相结合的边界点检测算法.该算法中网格技术用于快速查找数据集中聚类边界所在的网格范围,联合熵用于在边界落入的网格范围内准确识别聚类的边界点.实验结果表明.该算法能够在含有噪声点,孤立点的数据集上,有效地检测出聚类的边界,运行效率高.
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| 关 键 词： | 边界点 联合熵 网格 |
| 收稿时间： | 2009/11/2 0:00:00 |
| 修稿时间： | 2010/2/5 0:00:00 |
An efficient boundary points detecting algorithm based on joint entropy |
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| QIU Bao-zhi,CAO He-ling.An efficient boundary points detecting algorithm based on joint entropy[J].Control and Decision,2011,26(1):71-74. |
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| Authors: | QIU Bao-zhi CAO He-ling |
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| Affiliation: | (School of Information and Engineering, Zhengzhou University, Zhengzhou 450001,China.) |
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| Abstract: | In order to detect boundary points of clusters quickly and efficiently, a boundary points detecting
algorithm(EDGE) is proposed, which employs grid technique and joint entropy. Grid technique is used to search the scope of
grids which the boundary of clusters is located in and joint entropy is used to detect boundary points of clusters in these grids.
The experimental results show that EDGE can detect boundary points of clusters in datasets with noises/outliers effectively
and efficiently. |
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