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 ...

Our goal at The Upshot is to produce distinctive explanatory journalism. But how do we get there? Some of our best work starts with a reporter squinting at a table, or a list, or a rough chart, and ...

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, ...

This project consists in the implementation of the K-Means and Mini-Batch K-Means clustering algorithms. This is not to be considered as the final and most efficient algorithm implementation as the ...

Abstract: K-means clustering is a popular technique for partitioning a data set into subsets of similar features. Due to their simple control flow and inherent fine-grain parallelism, K-means ...