A fuzzy random forest: Fundamental for design and construction
Piero P. Bonissone, José Manuel Cadenas Figueredo, M. Carmen Garrido, R. A. D ́ iaz-Valladares · 2008
Following Breiman’s methodology, we propose a multi-classifier based on a “forest ” of randomly gener-ated fuzzy decision trees, i.e., a Fuzzy Random Forest. This ap-proach combines the robustness of multi-classifiers, the construction ef-ficiency of decision trees, the power of the randomness to increase the di-versity of the trees in the forest, and the flexibility of fuzzy logic and the fuzzy sets for data managing.