To find how many clusters in a sample set is an old yet unsolved problem in unsupervised clustering. Many segmentation methods require the user to specify the number of regions in...
Model-based clustering exploits finite mixture models for detecting group in a data set. It provides a sound statistical framework which can address some important issues, such as...
Consensus clustering is the problem of reconciling clustering information about the same data set coming from different sources or from different runs of the same algorithm. Cast ...
The diameter k-clustering problem is the problem of partitioning a finite subset of Rd into k subsets called clusters such that the maximum diameter of the clusters is minimized. ...
The metric 2-clustering problem is de ned as follows: given a metric (X;d), partition X into two sets S1 and S2 in order to minimize the value of X i X fu;vg Si d(u;v) In this pap...