James Omusula Atsali

Fuzzy Random Forest: Integrating Fuzzy Set Theory for Enhanced Imbalanced Classification

Fuzzy Random Forest is particularly suited for applications requiring high precision in minority class identification and interpretable fuzzy decision rules, such as medical diagnosis, fraud detection, and credit risk assessment where regulatory compliance demands transparent decision-making.