The study, “Using Artificial Intelligence to Determine the Impact of E-Commerce on the Digital Economy,” builds a fused indicator matrix spanning ICT infrastructure, payments, trade and logistics, ...

Data are clustered and ordered using a hierarchical clustering algorithm to aid with visualization of distinct community structures.

The Data Science Lab Data Clustering Using a Self-Organizing Map (SOM) with C# Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on technique for visualizing and ...

Entropy Minimization is a new clustering algorithm that works with both categorical and numeric data, and scales well to extremely large data sets.

Jeng-Min Chiou, Pai-Ling Li, Functional Clustering and Identifying Substructures of Longitudinal Data, Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 69, No. 4 ...

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, ...