Visual Studio Magazine

Data Clustering Using Entropy Minimization

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 ...
Visual Studio Magazine

Data Clustering Using a Self-Organizing Map (SOM) with C#

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 ...
Nature

Clustering in community structure across replicate ecosystems following a long-term bacterial evolution experiment

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 ...
JSTOR Daily

Model-based clustering of longitudinal data

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 38, No. 1 (March/mars 2010), pp. 153-168 (16 pages) A new family of mixture models for the model-based clustering of ...
JSTOR Daily

Model-Based Clustering of Non-Gaussian Panel Data Based on Skew- t Distributions

We propose a model-based method to cluster units within a panel. The underlying model is autoregressive and non-Gaussian, allowing for both skewness and fat tails, and the units are clustered ...