FBT models

FBT models, or Fuzzy Bayesian Theory models, combine fuzzy logic and Bayesian probability to handle uncertainty and imperfect information. They allow for flexible reasoning where data may be imprecise or uncertain, by assigning degrees of confidence to different hypotheses rather than strict yes/no answers. This approach improves decision-making in complex, real-world situations where not all information is clear-cut, enabling systems to make more nuanced and adaptive judgments based on partial or vague data.