The use of linked line segments for cluster representation and data reduction
Regardless of how one searches for clusters in data, the resulting cluster structures are often modelled as their respective centroids. However, the use of centroids in this manner implies the clusters are hyperspherical in shape. If the cluster shape is not hyperspherical, using the distance between individual observations and the centroid as a metric of an observation's cluster membership can be misleading. This report proposes the use of a linked line segment based model of cluster structure which is not biased towards any particular cluster shape. The effectiveness of the linked line segment approach is demonstrated in a data reduction exercise using simulated and real world data.
cluster representation data reduction density linkage cluster analysis k-means