A team of scientists at Northwest A and F University has developed a data-driven framework that can accurately predict the ...

Overview: Poor data validation, leakage, and weak preprocessing pipelines cause most XGBoost and LightGBM model failures in production.Default hyperparameters, ...

A machine learning model applied to US death certificate data estimated that over 155,000 COVID-19 deaths were unrecognized between March 2020 and December 2021, suggesting total mortality was about ...

A web-based system based on optimized models from 3 clinical scenarios may support clinical decision-making for personalized MPA therapy. A machine learning-driven framework accurately predicts ...

ABSTRACT: Accurate prediction of survey response rates is essential for optimizing survey design and ensuring high-quality data collection. Traditional methods often struggle to capture the complexity ...

Theft or unauthorised use of a credit card or the disclosure of sensitive financial information is known as credit card fraud. This massive financial crime affects consumers, businesses, and financial ...

Google launched four official and confirmed algorithmic updates in 2025, three core updates and one spam update. This is in comparison to last year, in 2024, where we had seven confirmed updates, then ...

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 ...

这是你suan的第一个项目，每日电力负荷的时间序列预测模型,数据集格式模板为：'年/月/日 时:分'(year/month/day hour:minute ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

The XGBoost-based approach demonstrated robust external validation across multiple centers, supporting clinical adoption to guide personalized treatment decisions. A machine learning (ML) model using ...