The use of bagging is explored to create an ensemble of fuzzy classifiers. The learning algorithm used was ANFIS (Adaptive Neuro-Fuzzy Inference Systems). We compare results from b...
Juana Canul-Reich, Larry Shoemaker, Lawrence O. Ha...
In this paper we propose computationally simple, pointwise formulas for extended t-norms and t-conorms on fuzzy truth values. The complex convolutions of the extended operations a...
Following Breiman’s methodology, we propose a multi-classifier based on a “forest” of randomly generated fuzzy decision trees, i.e., a Fuzzy Random Forest. This approach co...
This paper presents a fuzzy set theory based approach to Chinese sentence-level sentiment classification. Compared with traditional topic-based text classification techniques, the...
In spite of its successes as a tool in the field of engineering, fuzzy set theory has yet to achieve the universal footing that probability theory has across the various fields ...