Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
Journal of Computational and Applied Mathematics
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Topology representing networks
Neural Networks
Displaying a clustering with CLUSPLOT
Computational Statistics & Data Analysis
Cluster Analysis
A toolbox for K-centroids cluster analysis
Computational Statistics & Data Analysis
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Centroid-based partitioning cluster analysis is a popular method for segmenting data into more homogeneous subgroups. Visualization can help tremendously to understand the positions of these subgroups relative to each other in higher dimensional spaces and to assess the quality of partitions. In this paper we present several improvements on existing cluster displays using neighborhood graphs with edge weights based on cluster separation and convex hulls of inner and outer cluster regions. A new display called shadow-stars can be used to diagnose pairwise cluster separation with respect to the distribution of the original data. Artificial data and two case studies with real data are used to demonstrate the techniques.