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: 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, ...

Who needs a revamped Mac Pro when you can just turn several Mac Studios into a unified computing system? With the upcoming macOS Tahoe 26.2 release, Apple is introducing a new low-latency feature that ...

Mr. Means quietly departed his federal role about a month ago. His sister has been nominated for surgeon general. By Benjamin Mueller Calley Means, an influential adviser to Health Secretary Robert F.

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 ...

Abstract: Currently, a wide array of clustering algorithms have emerged, yet many approaches rely on K-means to detect clusters. However, K-means is highly sensitive to the selection of the initial ...

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 ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

To pick a bottle of wine can often feel like roulette, especially when wine terms like “malolactic fermentation” and “carbonic maceration” are involved. However, if you understand a few key ...