In this paper we discuss eNERF, an extended version of non-Euclidean relational fuzzy c-means (NERFCM) for approximate clustering in very large (unloadable) relational data. The e...
James C. Bezdek, Richard J. Hathaway, Christopher ...
In this paper, we propose a robust model selection criterion for mixtures of subspaces called minimum effective dimension (MED). Previous information-theoretic model selection cri...
Designing highly dependable systems requires a good understanding of failure characteristics. Unfortunately, little raw data on failures in large IT installations is publicly avai...
Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...
Active data clustering is a novel technique for clustering of proximity data which utilizes principles from sequential experiment design in order to interleave data generation and...