Predictive Performance

Predictive performance focuses on evaluating and improving the accuracy of models in forecasting future outcomes across diverse domains. Current research emphasizes robust methods that handle data variability and uncertainty, employing techniques like conformal prediction, ensemble methods (e.g., XGBoost), and large language models (LLMs) alongside traditional machine learning algorithms. This field is crucial for advancing various scientific disciplines and practical applications, from optimizing resource allocation in healthcare to enhancing financial forecasting and improving the efficiency of transportation systems.