PCA and K-means clustering applied to Raman and PL imaging reveal structural defects in silicon wafers, enhancing understanding of optoelectronic performance.

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

Abstract: This paper investigates the potential ofapproximate addition for k-means clustering, which is a popular unsupervised machine learning technique. The k-means clustering aims to organize data ...

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, ...

This project delivers a high-performance, scalable implementation of the StreamKM++ Paper (ACM Digital Library) streaming k-means clustering algorithm, redesigned with modern hardware in mind.

Abstract: The study utilizes a K-Means clustering analysis model to analyze the learning behavior data generated by online learners on an online learning platform ...

The Cleveland Guardians' successful pitching development group isn't a secret. They have a strong history of turning prospects into aces with long, successful careers. However, the Guardians are ...

ABSTRACT: Domaining is a crucial process in geostatistics, particularly when significant spatial variations are observed within a site, as these variations can significantly affect the outcomes of ...

ABSTRACT: The use of machine learning algorithms to identify characteristics in Distributed Denial of Service (DDoS) attacks has emerged as a powerful approach in cybersecurity. DDoS attacks, which ...