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 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 clustering data. A self-organizing map (SOM) is a data structure that can be used ...
Yahoo Finance

WiMi Launches Quantum-Assisted Unsupervised Data Clustering Technology Based on Neural Networks

BEIJING, Oct. 1, 2025 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced the ...
JSTOR Daily

Cluster–Robust Variance Estimation for Dyadic Data

Dyadic data are common in the social sciences, although inference for such settings involves accounting for a complex clustering structure. Many analyses in the social sciences fail to account for the ...
JSTOR Daily

A Feature-Based Approach to Market Segmentation Via Overlapping K-Centroids Clustering

Nonhierarchical partitioning techniques are used widely in many marketing applications, particularly in the clustering of consumers, as opposed to brands. These techniques can be extremely sensitive ...