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, ...

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 ...

Data clustering is the process of grouping data items so that similar items are placed in the same cluster. There are several different clustering techniques, and each technique has many variations.

As for hierarchical clustering, it’s useful when the underlying data has a hierarchical structure as it can often recover the hierarchy. However, it’s less efficient than k-means clustering.

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 ...

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, ...

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 ...