首页> 外文期刊>Information Technology Journal >Study on Mutual Information Based Clustering Algorithm
【24h】

Study on Mutual Information Based Clustering Algorithm

机译:基于互信息的聚类算法研究

获取原文
           

摘要

Traditional clustering algorithms are designed for isolated datasets. But in most cases, relationships among different datasets are always existed. So we must consider the actual circumstances from the cooperative aspects. A new collaborative model is proposed and based on this model a new cooperative clustering algorithm is presented. In theorem, the algorithm is proved to converge to the local minimum. Finally, experimental results demonstrate that the clustering structures obtained by new algorithm are different from those of conventional algorithms for the consideration of collaboration and the performances of these collaborative clustering algorithms can be much better than those traditional separated algorithms under the cooperating circumstances.
机译:传统的聚类算法是为孤立的数据集设计的。但是在大多数情况下,不同数据集之间的关系始终存在。因此,我们必须从合作方面考虑实际情况。提出了一种新的协作模型,并在此模型的基础上提出了一种新的协作聚类算法。定理证明该算法收敛于局部极小值。最后,实验结果表明,在协作条件下,新算法获得的聚类结构与常规算法不同,在协作环境下,这些聚类算法的性能要优于传统的分离算法。

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