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 ...

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 ...

Data clustering remains an essential component of unsupervised learning, enabling the exploration and interpretation of complex datasets. The field has witnessed considerable advancements that address ...

Virtualization and clustering can be two faces of the same coin. Computing virtualization is a very hot topic for data center managers. Whether the motivation is higher utilization, reduced management ...

Overview: Practical projects show how data supports real decisions across industries and services.Analytics skills grow ...