Cluster analysis can be performed with several models. One method is to seek those clusters for which the total flow between all within-cluster members is a maximum. This model has, until now, been viewed as mathematically difficult because of the presence of products of integer variables in the objective function. In another optimization model of cluster analysis, the p -median, a central member is found for each cluster, so that relationships of cluster members with the various central members are maximized (or minimized). This problem, although mathematically tractable, is a less realistic formulation of the general clustering problem. The formulation of the maximum interflow problem is here transformed in stages into a linear analogue w...
215 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.The study of the properties o...
Handbook of Cluster Analysis provides a comprehensive and unified account of the main research devel...
Determining an optimal number of clusters and producing reliable results are two challenging and cri...
Optimal clustering is a notoriously hard task. Recently, several papers have suggested a new approac...
Target of cluster analysis is to group data represented as a vector of measurements or a point in a ...
Target of cluster analysis is to group data represented as a vector of measurements or a point in a ...
We study the problem of finding an optimum clustering, a problem known to be NP-hard. Existing liter...
Target of cluster analysis is to group data represented as a vector of measurements or a point in a ...
We discuss a variety of clustering problems arising in combinatorial applications and in classifying...
In region building, different models of cluster analysis conform to different theoretical spatial st...
The objective functions in optimization models of the sum-of-squares clustering problem reflect intr...
The objective functions in optimization models of the sum-of-squares clustering problem reflect intr...
Partitioning data into a finite number of k homogenous and separate clusters (groups) without use of...
Abstract. We discuss a variety of clustering problems arising in combinatorial pplications and in cl...
<p>The optimal number of clusters for the STRUCTURE analysis shown in <a href="http://www.plosntds.o...
215 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.The study of the properties o...
Handbook of Cluster Analysis provides a comprehensive and unified account of the main research devel...
Determining an optimal number of clusters and producing reliable results are two challenging and cri...
Optimal clustering is a notoriously hard task. Recently, several papers have suggested a new approac...
Target of cluster analysis is to group data represented as a vector of measurements or a point in a ...
Target of cluster analysis is to group data represented as a vector of measurements or a point in a ...
We study the problem of finding an optimum clustering, a problem known to be NP-hard. Existing liter...
Target of cluster analysis is to group data represented as a vector of measurements or a point in a ...
We discuss a variety of clustering problems arising in combinatorial applications and in classifying...
In region building, different models of cluster analysis conform to different theoretical spatial st...
The objective functions in optimization models of the sum-of-squares clustering problem reflect intr...
The objective functions in optimization models of the sum-of-squares clustering problem reflect intr...
Partitioning data into a finite number of k homogenous and separate clusters (groups) without use of...
Abstract. We discuss a variety of clustering problems arising in combinatorial pplications and in cl...
<p>The optimal number of clusters for the STRUCTURE analysis shown in <a href="http://www.plosntds.o...
215 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.The study of the properties o...
Handbook of Cluster Analysis provides a comprehensive and unified account of the main research devel...
Determining an optimal number of clusters and producing reliable results are two challenging and cri...