...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Pattern recognition letters >Rough-DBSCAN: A fast hybrid density based clustering method for large data sets
【24h】

Rough-DBSCAN: A fast hybrid density based clustering method for large data sets

机译：Rough-DBSCAN：一种用于大型数据集的基于快速混合密度的聚类方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Density based clustering techniques like DBSCAN are attractive because it can find arbitrary shaped clusters along with noisy outliers. Its time requirement is 0(n~2) where n is the size of the dataset, and because of this it is not a suitable one to work with large datasets. A solution proposed in the paper is to apply the leaders clustering method first to derive the prototypes called leaders from the dataset which along with prototypes preserves the density information also, then to use these leaders to derive the density based clusters. The proposed hybrid clustering technique called rough-DBSCAN has a time complexity of 0(n) only and is analyzed using rough set theory. Experimental studies are done using both synthetic and real world datasets to compare rough-DBSCAN with DBSCAN. It is shown that for large datasets rough-DBSCAN can find a similar clustering as found by the DBSCAN, but is consistently faster than DBSCAN. Also some properties of the leaders as prototypes are formally established.
机译：基于密度的聚类技术（例如DBSCAN）具有吸引力，因为它可以找到任意形状的聚类以及嘈杂的异常值。它的时间要求是0（n〜2），其中n是数据集的大小，因此，它不适合用于大型数据集。本文提出的解决方案是首先应用领导者聚类方法从数据集中导出称为领导者的原型，然后与原型一起保存密度信息，然后使用这些领导者来导出基于密度的聚类。提出的称为粗糙DBSCAN的混合聚类技术的时间复杂度仅为0（n），并使用粗糙集理论进行了分析。使用合成数据集和实际数据集进行了实验研究，以比较粗略的DBSCAN和DBSCAN。结果表明，对于大型数据集，粗略的DBSCAN可以找到与DBSCAN相似的聚类，但是始终比DBSCAN快。还正式确定了领导者作为原型的某些属性。

著录项

  • 来源
    《Pattern recognition letters》 |2009年第16期|1477-1488|共12页
  • 作者

    P. Viswanath; V. Suresh Babu;

  • 作者单位

    Pattern Recognition Research Lab, Department of Computer Science and Engineering, NRI Institute of Technology, Guntur 522 009, Andhra Pradesh, India;

    Institute for Research in Applicable Computing, Department of Computing and Information Systems, University of Bedfordshire, Luton Campus, Park Square, Luton, LU1 3JU, UK;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    clustering; density based clustering; DBSCAN; leaders; rough sets;

    机译：集群基于密度的聚类;DBSCAN;领导者粗糙集;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号