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Abstract: In a bivariate data set it is easy to represent clusters, e.g. by manually circling them or separating them by lines. But many data sets have more than two variables, or they come in the form of inter-object dissimilarities. There exist methods to partition such a data set into clusters, but the resulting partition is not visual by itself. In this paper we construct a new graphical display called CLUSPLOT, in which the objects are represented as points in a bivariate plot and the clusters as... (Update)
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.... is proportional to the cluster density (number of class members divided by the area of the ellipse) Clusplot is described in detail in [21]. 3.5.2 Silhouette plot Silhouette plots (see for example [25] visualize the quality of the clustering for every object separately...
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BibTeX entry: (Update)
G. Pison, A. Stuyf, P.J. Rousseew, Displaying a clustering with CLUSPLOT. Computational Statistics & Data Analysis 30, 381 - 392 (1999). http://citeseer.ist.psu.edu/pison98displaying.html More
@misc{ pison99displaying,
author = "G. Pison and A. Stuyf and P. Rousseew",
title = "Displaying a clustering with CLUSPLOT",
text = "G. Pison, A. Stuyf, P.J. Rousseew, Displaying a clustering with CLUSPLOT.
Computational Statistics & Data Analysis 30, 381 - 392 (1999).",
year = "1999",
url = "citeseer.ist.psu.edu/pison98displaying.html" }
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