In this paper, an evolutionary clustering technique is described that uses a new point symmetry-based distance measure. The algorithm is therefore able to detect both convex and n...
In this paper we present a method to cluster large datasets that change over time using incremental learning techniques. The approach is based on the dynamic representation of clus...
Parallel coordinates have been widely applied to visualize high-dimensional and multivariate data, discerning patterns within the data through visual clustering. However, the effe...
Hong Zhou, Xiaoru Yuan, Huamin Qu, Weiwei Cui, Bao...
The clustering algorithm DBSCAN relies on a density-based notion of clusters and is designed to discover clusters of arbitrary shape as well as to distinguish noise. In this paper,...
We propose a simple probabilistic generative model for image segmentation. Like other probabilistic algorithms (such as EM on a Mixture of Gaussians) the proposed model is princip...