A generalized framework for ANFIS synthesis procedures by clustering techniques
The application of machine learning and soft computing techniques for function approximation is a widely explored topic in literature. Neural networks, evolutionary algorithms and support vector machines proved to be very effective, although these models suffer from very low level of interpretability by human operators. Conversely, Adaptive Neuro Fuzzy Inference Systems (ANFISs) demonstrated to be very accurate models featured by a considerable degree of interpretability. In this paper, a general framework for ANFIS training by clustering is proposed and investigated.