IEEE

A Novel Transfer Learning Framework Combining Attention Mechanisms and Random Forest Regression for State of Health Estimation of Lithium-Ion Battery With Different Formulations

Abstract: Accurate and reliable state of health (SOH) estimation is essential to ensure the stable and safe operation of lithium-ion batteries. The SOH estimation for batteries with different ...
Devdiscourse

Stacked AI model improves credit default forecasting

A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...
IEEE

An Improved Random Forest Algorithm (ERFA) Utilizing an Unbalanced and Balanced Dataset to Predict Customer Churn in the Banking Sector

Abstract: Customer churn, the phenomenon of customers discontinuing their relationship with a company, poses significant challenges for businesses in various industries, including the banking sector.
RMD Open

Distinct pattern of comorbidities hinders treatment target attainment in SLE through persistent disease activity and delayed glucocorticoid tapering: longitudinal data fro…

Background Remission and low-disease activity are recommended targets in systemic lupus erythematosus (SLE), yet many ...
Science Daily

Forests are changing fast and scientists are deeply concerned

Forests around the world are quietly transforming, and not for the better. A massive global analysis of more than 31,000 tree species reveals that forests are becoming more uniform, increasingly ...
GitHub

random-forest-scikit-learn-python-gradio

Machine Learning project to predict water potability using supervised learning algorithms with data preprocessing, model comparison, and deployment using Gradio. Gradio. data preprocessing, model ...