The deal paves the way for TikTok to escape legal peril months after a U.S. ban. Social media giant TikTok struck an agreement to put its U.S. operations under the majority control of U.S. investors, ...

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, ...

Abstract: For radar signal sorting based on pulse descriptors, the inherent limitations of the traditional K-means algorithm include the requirement of a predefined number of clusters, the sensitivity ...

Rocky high steep slopes are among the most dangerous disaster-causing geological bodies in large-scale engineering projects, like water conservancy and hydropower projects, railway tunnels, and metal ...

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 ...

A high-performance Parallel K-Means Clustering algorithm implemented in C++ with OpenMP for parallelization. This project demonstrates the use of advanced clustering techniques with efficient ...

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 ...

A K-Means algorithm implementation involving various optimization techniques. Used to group MNIST dataset of hand-written numbers 0-9.