The Detroit Pistons bounced back in style, beating the New Orleans Pelicans 129-108 on Thursday night. After falling to the Atlanta Hawks in a 130-129 overtime thriller the night prior, the Pistons ...

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, ...

This repository contains computational notebooks and analysis code for research on smart K-means clustering algorithms applied to social exclusion indicators. The project implements and compares ...

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: In order to solve the problem that the initial K value of K-Means clustering algorithm needs to be given in advance and the division needs to be determined according to the initial ...

ABSTRACT: Domaining is a crucial process in geostatistics, particularly when significant spatial variations are observed within a site, as these variations can significantly affect the outcomes of ...

Clustering algorithms are at the basis of several technological applications, and are fueling the development of rapidly evolving fields such as machine learning. In the recent past, however, it has ...

Abstract: In this paper, an improved K-means clustering algorithm, EGLK-Means, is proposed, which optimizes the clustering results by enhancing global and local information. The traditional K-means ...

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 ...