Neutrosophic Ensemble Classification

A method that decomposes the prediction outputs of ensemble machine learning models using neutrosophic logic, breaking down confidence into four independent dimensions: evidence strength (T-hat), competition strength (F-hat), prediction entropy (I1-hat), and ensemble disagreement (I2-hat), enabling more granular uncertainty quantification.