An Experimental Study of Partition Quality Indices in Clustering

Authors:
Céline Robardet;Fabien Feschet;Nicolas Nicoloyannis
Affiliations:
-;-;-
Venue:
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Year:
2000

Citing 5
Cited 0

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Abstract

We present a preliminary study to define a comparison protocol to evaluate different quality measures used in supervised and unsupervised clustering as objective functions. We first define an order on the set of partitions to capture the common notion of a good partition towards the knowing of the ideal one. We demonstrate the efficiency of this approach by providing several experiments.