IEEE

Neural-XGBoost: A Hybrid Approach for Disaster Prediction and Management Using Machine Learning

Abstract: Effective disaster prediction is essential for disaster management and mitigation. This study addresses a multi-classification problem and proposes the Neural-XGBoost disaster prediction ...
CoinDesk

How AI is helping retail traders exploit prediction market 'glitches' to make easy money

A fully automated bot quietly captured micro-arbitrage opportunities on short-term crypto prediction markets, netting nearly ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
InfoWorld

How to choose the best LLM using R and vitals

Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models.
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
IEEE

Federated Learning Intersection Vehicle Trajectory Prediction Scheme Within Digital Twin

Abstract: Digital Twin (DT) technology has gained significant attention for simulating and optimizing urban traffic systems, especially in intersection vehicle trajectory prediction. However, digital ...