| 支持k-离群度的边界点检测方法 |
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| 引用本文： | 王桂芝,李井竹,狄志超. 支持k-离群度的边界点检测方法[J]. 计算机工程与应用, 2011, 47(33): 140-142. DOI: 10.3778/j.issn.1002-8331.2011.33.041 |
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| 作者姓名： | 王桂芝 李井竹 狄志超 |
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| 作者单位： | 1.河南商业高等专科学校 计算机应用系，郑州 4500442.郑州大学 信息工程学院，郑州 450052 |
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| 基金项目： | 河南省高等学校青年骨干教师资助计划项目(No.2010GGJS-200) |
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| 摘 要： | 边界是一种有用的模式，为了有效识别边界，根据边界点周围密度不均匀，提出了一种边界点检测算法——BDKD。该算法用数据对象的k-近邻距离与其邻域内数据对象的平均k-近邻距离之比定义其k-离群度，当k-离群度超过阈值时即确定为边界点。实验结果表明，BDKD算法可以准确检测出各种聚类边界，并能去除噪声，特别是对密度均匀的数据集效果理想。
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| 关 键 词： | 聚类 边界点 k-近邻距离 k-离群度 边界因子 |
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Boundary detection method in support of k-outlier degree |
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| WANG Guizhi,LI Jingzhu,DI Zhichao. Boundary detection method in support of k-outlier degree[J]. Computer Engineering and Applications, 2011, 47(33): 140-142. DOI: 10.3778/j.issn.1002-8331.2011.33.041 |
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| Authors: | WANG Guizhi LI Jingzhu DI Zhichao |
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| Affiliation: | 1.Department of Computer Application，Henan Business College，Zhengzhou 450044，China2.School of Information Engineering，Zhengzhou University，Zhengzhou 450052，China |
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| Abstract: | Border is a useful model.In order to detect the boundaries of various shapes effectively,based on the uneven density around the border point,this paper proposes a boundary detection algorithm—BDKD.This algorithm defines the ratio of k-nearest neighbor distance of data objects to the average neighborhood of them as their k-outlier degrees.They are identified as boundary points when the k-outlier of them exceeds the threshold.The results show that BDKD algorithm can accurately detect the boundaries of various clusters and remove the noises.In particular,BDKD algorithm is suitable for the data set of uniform density satisfactorily. |
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| Keywords: | clustering border point k-nearest neighbor distance k-outlier degrees border factor
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