Ensemble clustering methods combine multiple clustering results to yield a consensus partition that is often more robust, accurate and stable than any single clustering solution. These techniques ...

Many simulation studies comparing various methods of cluster analysis have been performed. In these studies, artificial data sets containing known clusters are produced using pseudo-random-number ...

The study shows how probabilistic clustering supports intelligent data transmission strategies. The authors propose leveraging cluster probabilities to define transmission rules: sensors with a high ...

Data clustering is the process of placing data items into groups so that items within a group are similar and items in different groups are dissimilar. The most common technique for clustering numeric ...

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 ...

A vast region of our solar system, called the Kuiper belt, stretches from the orbit of Neptune out to 50 or so astronomical units (AU), where an AU is the distance between Earth and the sun. This ...