Cluster analysis using triangulation

摘要

Cluster analysis has been a topic researched for some time now. However many clustering algorithms suffer from a significant in that they assume that the underlying clusters are spherical. Unfortunately, this is not appropriate for all data sets. This paper looks at clustering using tools from graph theory. It first triangulates the data, then partitions the edges of the resulting graph into inter-and intra-cluster edges. The technique is unaffected by the actual shape of the clusters, thus allowing a far more general version of the clustering problem to be solved.