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最小平均成本聚类

Minimum Average Cost Clustering
课程网址: http://videolectures.net/nips2010_nagano_macc/  
主讲教师: Kiyohito Nagano
开课单位: 东京工业大学
开课时间: 2011-03-25
课程语种: 英语
中文简介:
可以使用子模块函数描述聚类问题中的许多目标函数。在本文中,我们引入最小平均成本标准,并表明交叉子模函数的理论可用于具有子模块目标函数的聚类。所提出的算法不需要预先提供簇的数量,并且它将由给定数据点集的属性确定。最小平均成本聚类问题用实变量参数化,并且令人惊讶的是,我们显示所有参数的最佳聚类的所有信息可以在多项式时间内计算。此外,我们通过计算实验评估了所提算法的性能。
课程简介: A number of objective functions in clustering problems can be described with submodular functions. In this paper, we introduce the minimum average cost criterion, and show that the theory of intersecting submodular functions can be used for clustering with submodular objective functions. The proposed algorithm does not require the number of clusters in advance, and it will be determined by the property of a given set of data points. The minimum average cost clustering problem is parameterized with a real variable, and surprisingly, we show that all information about optimal clusterings for all parameters can be computed in polynomial time in total. Additionally, we evaluate the performance of the proposed algorithm through computational experiments.
关 键 词: 子模块函数; 最小平均成本; 最佳聚类
课程来源: 视频讲座网
最后编审: 2020-10-22:chenxin
阅读次数: 86