CybernewsOpinion

World in crisis: why is JD Vance talking about aliens and can you trust your code?

As President Donald Trump wages his war of choice in the Middle East, he has his lieutenants, Defence Secretary Pete Hegseth ...
Analytics Insight

Machine Learning, Stanford University

Stanford University’s Machine Learning (XCS229) is a 100% online, instructor-led course offered by the Stanford School of ...
GitHub

What is Unsupervised Learning?

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...
Mashable

TikTok deal adds new U.S. owners. Here's what this means for users.

TikTok will officially remain in the U.S. for the foreseeable future. A new, majority U.S.-owned company had been established to continue running the popular video-sharing app in the country, and has ...
Frontiers

K-means classification of long-term global vegetation index variation

Recent global warming has driven substantial changes in terrestrial vegetation, yet long-term global patterns remain insufficiently characterized. The Normalized Difference Vegetation Index (NDVI) ...
The New York Times

Can J.K. Dobbins return for the playoffs? What it would mean for Broncos’ run game

J.K. Dobbins could give Denver a big playoff boost. Matthew Stockman / Getty Images J.K. Dobbins has the kind of smile that produces other smiles. His wide grin is contagious, and as he ran for 772 ...
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, ...
Scientific Research Publishing

Wang, Q., Wang, C., Feng, Z. Y. et al. (2012). Survey of K-Means Clustering Algorithm Research. Electronic Design Engineering, 20, 21-24. (In Chinese)

ABSTRACT: From the perspective of student consumption behavior, a data-driven framework for screening student loan eligibility was developed using K-means clustering analysis and decision tree models.
IEEE

Research on Improved k-Means Clustering Algorithm Based on Density-Weighted Canopy

Abstract: This paper proposes an improved K-means clustering algorithm based on density-weighted Canopy to address the efficiency bottlenecks and clustering accuracy issues commonly encountered by ...
Scientific Research Publishing

Applying K-Means Clustering and Fuzzy C-Means Clustering in Vehicle Crashes ()

Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering algorithms to a ...
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, ...