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 ...

Clustering non-numeric -- or categorial -- data is surprisingly difficult, but it's explained here by resident data scientist Dr. James McCaffrey of Microsoft Research, who provides all the code you ...

Compared to other clustering techniques, DBSCAN does not require you to explicitly specify how many data clusters to use, explains Dr. James McCaffrey of Microsoft Research in this full-code, ...

In materials science, substances are often classified based on defining factors such as their elemental composition or crystalline structure. This classification is crucial for advances in materials ...

Brien details the pros and cons of Hyper-V replication versus clustering, and what scenarios work best for each method. For several years now, I have been using Hyper-V's replication feature to ...