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.

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, ...

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, ...

One of the main challenges of any online business is to get actionable insight from their data for decision-making. Spotify shares its methodology and experience to solve this problem by ...

Multilevel data are structures that consist of multiple units of analysis, one nested within the other. Such data are becoming quite common in political science and provide numerous opportunities for ...