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Unformatted text preview: see Fickel
(1997); Duda & Hart (1973)). One of the most well-known measures is the mean
square error. It permits to make statements on quality of the found clusters
dependent on the number of clusters. Unfortunately, the computed quality
is always better if the number of cluster is higher. In Kaufman & Rousseeuw
(1990) an alternative measure, the silhouette coefﬁcient, is presented which is
independent of the number of clusters. We introduce both measures in the
Statistical Measures If one keeps the number of dimensions and the number of
clusters constant the mean square error (Mean Square error, MSE) can be used Mean square error Band 20 – 2005 37 Hotho, Nürnberger, and Paaß
likewise for the evaluation of the quality of clustering. The mean square error is
a measure for the compactness of the clustering and is deﬁned as follows:
Deﬁnition 1 (MSE) The means square error ( MSE) for a given clustering P is deﬁned
MSE(P ) = ∑ MSE( P),
P ∈P whereas the means...
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This note was uploaded on 06/19/2011 for the course IT 2258 taught by Professor Aymenali during the Summer '11 term at Abu Dhabi University.
- Summer '11