A Fuzzy Random Forest: Fundamental for Design and Construction

P. Bonissone, J.M. Cadenas, M.C. Garrido, R.A. Díaz-Valladares.

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 combines the robustness of multi-classifiers, the construction efficiency of decision trees, the power of the randomness to increase the diversity of the trees in the forest, and the flexibility of fuzzy logic and the fuzzy sets for data managing.

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