Northwestern's McCormick School of Engineering

Adaptive Algorithm Aims to Reduce Kidney Discards and Improve Transplant Access

Developed by Professor Sanjay Mehrotra, the Sliding Scale AdaptiVe Expedited (SAVE) algorithm could improve organ allocation ...
Scientific Research Publishing

Ahmed, M., Seraj, R. and Islam, S.M.S. (2020) The K-Means Algorithm: A Comprehensive Survey and Performance Evaluation. Electronics, 9, Article No. 1295.

ABSTRACT: Under the context of urban compound air pollution, the joint dependence structure and spatiotemporal characteristics between NO2 and PM2.5 have not yet been systematically quantified. To ...
Kotaku

The Empathy Algorithm

All the Latest Game Footage and Images from The Empathy Algorithm Are you an android? Two university students volunteer for a paid experiment, rating an android’s humanity—except Erin Cole isn’t told ...
GitHub

What is Unsupervised Learning?

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...
IEEE

Centroid-Free K-Means With Balanced Clustering

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 ...
The New York Times

Can J.K. Dobbins return for the playoffs? What it would mean for Broncos’ run game

J.K. Dobbins could give Denver a big playoff boost. Matthew Stockman / Getty Images J.K. Dobbins has the kind of smile that produces other smiles. His wide grin is contagious, and as he ran for 772 ...
Visual Studio Magazine

Anomaly Detection Using K-Means Clustering with JavaScript

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, ...
IEEE

Research on Improved k-Means Clustering Algorithm Based on Density-Weighted Canopy

Abstract: This paper proposes an improved K-means clustering algorithm based on density-weighted Canopy to address the efficiency bottlenecks and clustering accuracy issues commonly encountered by ...
Scientific Research Publishing

Applying K-Means Clustering and Fuzzy C-Means Clustering in Vehicle Crashes ()

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 ...