On his second inauguration day, in January 2025, President Donald Trump signaled one of his administration's highest priorities by issuing an executive order titled "Protecting the American People ...

Ballot (Balanced Lloyd with Optimal Transport) is a high-performance Python package for balanced clustering. It solves the problem of creating equal-sized clusters (or clusters with specific capacity ...

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

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, ...

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 ...

Abstract: The paper presents a detailed research study of the k-means clustering algorithm to be used for image compression tasks, where the RGB values of the colors are considered XYZ coordinates of ...

Implement a K-Means clustering algorithm using Python and apply it to a well-known clustering dataset (e.g., Mall Customers, Wholesale Customers, or any publicly available dataset). This task will ...

Abstract: K-means is a commonly used algorithm in machine learning. It is an unsupervised learning algorithm. It is regularly used for data clustering. Only the number of clusters are needed to be ...