Multilayer Ensemble Evolving Fuzzy Inference System

In order to tackle high dimensional, complex problems, learning models have go deeper. this article, a novel multilayer ensemble model with first-order evolving fuzzy systems as its building blocks is introduced. The proposed approach can effectively learn from streaming data on sample-by-sample basis and self-organizes multilayered system structure meta-parameters in feedforward, noniterative manner. Benefiting distributed representation ability, the not only demonstrates state-of-the-art performance various but also offers level of transparency explainability. Theoretical justifications experimental investigation show validity effectiveness concept general principles.