The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
We present an online adaptive clustering algorithm in a decision tree framework which has an adaptive tree and a code formation layer. The code formation layer stores the represen...
This paper proposes a novel hierarchical clustering method that can classify given data without specified knowledge of the number of classes. In this method, at each node of a hie...
With hierarchical clustering methods, divisions or fusions, once made, are irrevocable. As a result, when two elements in a bottom-up algorithm are assigned to one cluster, they c...
The calculation of radiant energy balance in complex scenes has been made possible by hierarchical radiosity methods based on clustering mechanisms. Although clustering offers an ...