Data clustering, or cluster analysis, is the process of grouping data items so that similar items belong to the same group/cluster. There are many clustering techniques. In this article I'll explain ...

If your data is completely numeric, then the k-means technique is simple and effective. But if your data contains non-numeric data (also called categorical data) then clustering is surprisingly ...

Traditional clustering methods often fail when faced with complex, non-linear data patterns. This is where density-based clustering comes into play.

Apache Spark, the big data processing framework that is a fixture of many Hadoop installs, has reached its 1.4 incarnation. With it comes support for R and Python 3 — two languages in wide use ...

A collaboration of researchers from the University of California Davis, the National Energy Research Scientific Computing Center, and Intel are working together on the DisCo project to extract insight ...

We introduce a novel statistical procedure for clustering categorical data based on Hamming distance (HD) vectors. The proposed method is conceptually simple and computationally straightforward, ...