Devdiscourse

Banks could strengthen credit card fraud screening with ensemble machine learning model

Read more about Banks could strengthen credit card fraud screening with ensemble machine learning model on Devdiscourse ...

How Explainable AI Is Reshaping Insurance Fraud Detection

Yeshwanth Macha developed explainable AI models improving insurance fraud detection accuracy, transparency, compliance and ...
Hosted on MSN

AI ensemble models sharpen NBA game predictions and strategy

New research using AI-powered stacked ensemble models has improved accuracy in predicting NBA game results by combining multiple machine learning algorithms. These models not only forecast outcomes ...
IEEE

Explainable Machine Learning for Sleep Health Analysis Using XGBoost and SHAP Interpretability

With the integration of machine learning techniques into the medical field, there has been a sea change in the last couple of years, and a new era of innovation seems to usher in precision healthcare ...
IEEE

Real-time Analysis of DDoS Attack Detection and Mitigation Measures Using XGBoost Machine Learning Algorithm

Abstract: Distributed Denial of Service (DDoS) attacks pose an ongoing threat to networked systems, often disrupting services and compromising data integrity. This study presents a real-time approach ...
Scientific Research Publishing

Dinov, I. D. (2023). Model Performance Assessment, Validation, and Improvement. In editor (Ed.), The Springer Series in Applied Machine Learning (Vol. 2853, pp. 477-531 ...

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 ...
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 ...
Scientific Research Publishing

Liang, W., Luo, S., Zhao, G. and Wu, H. (2020) Predicting Hard Rock Pillar Stability Using GBDT, XGBoost, and LightGBM Algorithms. Mathematics, 8, Article No. 765.

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 ...