Visual Studio Magazine

Anomaly Detection Using K-Means Clustering with JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...
The New York Times

Calley Means Returns to Kennedy’s Side as Senior Adviser

Mr. Means, who co-founded a wellness company, has emerged as one of the most prominent voices in the Make America Healthy Again movement. By Dani Blum Calley Means, a health care entrepreneur and key ...
GitHub

IfyQ/DS_Hierarchical_Clustering

This project applies hierarchical clustering to group local authorities in England based on case closure reasons from the Children in Need Census (2013–2024). It supports benchmarking, policy ...
Scientific Research Publishing

Tabianan, K., Velu, S. and Ravi, V. (2022) K-Means Clustering Approach for Intelligent Customer Segmentation Using Customer Purchase Behavior Data. Sustainability, 14, Article ...

ABSTRACT: Doping is an issue associated with elite sports as athletes attempt to enhance their performance to gain an edge over other athletes. However, the prevalence of doping is continuously ...
IEEE

A Topological-Indicators-Based k-Means Clustering Algorithm and Its Application in Time Series Data: A Case Study on Sea Level Variability in Peninsular Malaysia

Abstract: Traditional k-means clustering is widely used to analyze regional and temporal variations in time series data, such as sea levels. However, its accuracy can be affected by limitations, ...
IEEE

Codebook-Based Trellis-Coded Quantization Scheme Using K-Means Clustering for Massive MIMO Systems

Abstract: This paper introduces a codebook-based trellis-coded quantization (TCQ) approach utilizing K-means clustering, designed specifically for massive multiple-input multiple-output systems. The ...