Entropy Minimization is a new clustering algorithm that works with both categorical and numeric data, and scales well to extremely large data sets. Data clustering is the process of placing data items ...

Experiments to date probing adaptive evolution have predominantly focused on studying a single species or a pair of species in isolation. In nature, on the other hand, species evolve within complex ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on technique for visualizing and clustering data. A self-organizing map (SOM) is a data structure that can be used ...

A new family of mixture models for the model-based clustering of longitudinal data is introduced. The covariance structures of eight members of this new family of models are given and the associated ...

In this article we focus on clustering techniques recently proposed for high-dimensional data that incorporate variable selection and extend them to the modeling of data with a known substructure, ...

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