Fuzzy regression models extend traditional statistical regression by integrating fuzzy set theory to better handle imprecision and uncertainty inherent in many real-world data sets. These models ...

Built on a new architecture KumoRFM-2 achieves state-of-the-art results across 41 predictive tasks and four major benchmarks, ...

Innovative machine learning models using routine clinical data offer superior stroke risk prediction in atrial fibrillation, ...

What was the rationale behind applying machine learning (ML) models to improve identification probability in the absence of ...

Forecasting inflation has become a major challenge for central banks since 2020, due to supply chain disruptions and economic uncertainty post-pandemic. Machine learning models can improve forecasting ...

The increasing global demand for sustainable energy and carbon materials, alongside pressing environmental concerns, ...