Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.

Machine learning models delivered the strongest performance across nearly all evaluation metrics. CHAID and CART provided the highest and most stable sensitivity, accuracy and discriminatory power, ...

This prediction approach achieves higher agreement in predictions by optimizing the concordance correlation coefficient (CCC), which measures how well pairs of observations fall on the 45-degree line ...

Prediction markets act as a leading indicator for inflation data, a new report finds. Traders are incorporating Polymarket ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

Prediction markets quadrupled resting capital to $13B in 2025 despite volume volatility, proving they're exchanges for ...

Objective To develop prediction models for short-term outcomes following a first acute myocardial infarction (AMI) event (index) or for past AMI events (prevalent) in a national primary care cohort.

Injury Probability Models Explained. Learn how smart data and clear numbers improve sports prediction while protecting ...