首页> 外文会议>International conference on advanced data mining and applications;ADMA 2010 >A Novel Clustering Algorithm Based on Gravity and Cluster Merging
【24h】

A Novel Clustering Algorithm Based on Gravity and Cluster Merging

机译:一种基于重力和聚类融合的聚类算法

获取原文

摘要

Fuzzy C-means (FCM) clustering algorithm is commonly used in data mining tasks. It has the advantage of producing good modeling results in many cases. However, it is sensitive to outliers and the initial cluster centers. In addition, it could not get the accurate cluster number during the algorithm. To overcome the above problems, a novel FCM algorithm based on gravity and cluster merging was presented in this paper. By using gravity in this algorithm, the influence of outliers was minimized and the initial cluster centers were selected. And by using cluster merging, an appropriate number of clustering could be specified. The experimental evaluation shows that the modified method can effectively improve the clustering performance.
机译:模糊C均值(FCM)聚类算法通常用于数据挖掘任务。在许多情况下,它具有产生良好建模结果的优势。但是,它对异常值和初始聚类中心很敏感。另外,在算法过程中无法获得准确的簇数。针对上述问题,提出了一种基于重力和聚类融合的FCM算法。通过在算法中使用重力,离群值的影响被最小化,并选择了初始聚类中心。通过使用群集合并,可以指定适当数量的群集。实验评估表明,改进后的方法可以有效提高聚类性能。

著录项

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