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 with K-Means Using Python

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 ...
JSTOR Daily

Bayesian Variable Selection in Clustering High-Dimensional Data with Substructure

In this article we focus on clustering techniques recently proposed for high-dimensional data that incorporate variable selection and extend them to the modeling of data with a known substructure, ...
JSTOR Daily

Predicting Clustering from Semantic Structure

This study presents a process model for predicting the strength of semantic clustering within homogeneous semantic domains. The key element of the model is the assumption that clustering between ...