Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
The American Journal of Managed Care

Machine Learning–Based Predictors for RA Relapse Evaluated

Researchers found that the extreme gradient boosting (XGBoost) predictor could more accurately predict rheumatoid arthritis (RA) relapse than logistic regression and random forest. When evaluating ...
pv magazine International

Machine learning method to identify residential PV adopters, reduce soft costs

An international research team has utilized a machine learning algorithm known as XGBoost (eXtreme Gradient Boosting) to predict PV adoption among homeowners. This algorithm consists of a distributed ...
EurekAlert!

Intelligent XGBoost framework enhances asphalt pavement skid resistance assessment

Researchers have developed a novel AI-driven framework using the XGBoost algorithm to accurately evaluate the skid resistance of asphalt pavements under various conditions. Published in Smart ...
InfoWorld

Time series forecasting with XGBoost and InfluxDB

XGBoost is a popular open source machine learning library that can be used to solve all kinds of prediction problems. Here’s how to use XGBoost with InfluxDB. XGBoost is an open source machine ...
ascopubs.org

Prediction of Patients With High-Risk Osteosarcoma on the Basis of XGBoost Algorithm Using Transcriptome and Methylation Data From SGH-OS Cohort

Benefits of Combining Circulating Tumor DNA With Tissue and Longitudinal Circulating Tumor DNA Genotyping in Advanced Solid Tumors: SCRUM-Japan MONSTAR-SCREEN-1 Study Osteosarcoma (OS) is the most ...