Scientific Research Publishing

Boosting Algorithm: An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ()

An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
Analytics Insight

Best Tools to Visualize and Understand Machine Learning Models: Top Picks

Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...
Game Rant

How to Destroy All ARC Machines Fast (Weak Points) in ARC Raiders

Ayyoun is a staff writer who loves all things gaming and tech. His journey into the realm of gaming began with a PlayStation 1 but he chose PC as his platform of choice. With over 6 years of ...
Frontiers

Ensemble machine learning for predicting renal function decline in chronic kidney disease: development and external validation

1 Department of Nephrology, the 95th Hospital of Putian in China RongTong Medical Health Corporation, Putian, China 2 Department of Rheumatology and Immunology, the 95th Hospital of Putian in China ...
IEEE

Utilization of Ensemble Techniques in Machine Learning to Predict the Porosity and Hardness of Plasma-Sprayed Ceramic Coating

Abstract: Ceramic coatings play a vital role in protecting steel components by significantly enhancing their corrosion and wear resistance, thereby extending service life. The performance of these ...
Scientific Research Publishing

A Comparative Study of Ensemble Learning Techniques and Classification Models to Identify Phishing Websites ()

The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by security ...
Eos

Calibrating Climate Models with Machine Learning

Climate models are essential tools for understanding and predicting our planet, but accurately setting their many internal parameters is complex and has been a labor-intensive manual task in the past.