Nature

Hyperspectral imaging and K-means clustering for material structure classification and detection of unmanned aerial vehicles

Unmanned aerial vehicles (UAVs) have become increasingly widespread in a variety of industries due to their versatility and efficiency in applications such as agriculture, surveillance, logistics, and ...
Nature

Enhancing classification accuracy in medical datasets using a hybrid distance and cluster refinement-based K-means clustering method

Machine learning methods, especially the K_Means clustering method, have demonstrated potential in analyzing medical data by facilitating pattern detection. However, the classic K_Means algorithm ...
Semiconductor Engineering

Spark On AWS Graviton2 Best Practices: K-Means Clustering Case Study

This report focuses on how to tune a Spark application to run on a cluster of instances. We define the concepts for the cluster/Spark parameters, and explain how to configure them given a specific set ...
Visual Studio Magazine

Clustering Mixed Categorical and Numeric Data Using k-Means with C#

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a "very tricky" machine learning technique. Data clustering is the process of grouping data items together so ...
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, ...