Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
This paper presents a general framework for adapting any generative (model-based) clustering algorithm to provide balanced solutions, i.e., clusters of comparable sizes. Partition...
This paper presents a simple but powerful extension of the maximum margin clustering (MMC) algorithm that optimizes multivariate performance measure specifically defined for clust...
Order-preserving submatrixes (OPSMs) have been accepted as a biologically meaningful subspace cluster model, capturing the general tendency of gene expressions across a subset of ...
Byron J. Gao, Obi L. Griffith, Martin Ester, Steve...
Spatial clustering is an active research area in spatial data mining with various methods reported. In this paper, we compare two density-based methods, DBSCAN and DBRS. First, we ...