This chapter provides an all-round picture of the development and advances in the fields of
evolving fuzzy systems (EFS) and evolving neuro-fuzzy systems (ENFS) which have been …

Evolving classifiers and especially evolving fuzzy classifiers have been established as a
prominent technique for addressing the recent demands in building classifiers in an …

Multi-label classification has attracted much attention in the machine learning community to
address the problem of assigning single samples to more than one (not necessarily non …

In this paper, a new interval type-2 fuzzy neural network able to construct non-separable
fuzzy rules with various shapes is introduced for function approximation problems. To reflect …

Data stream classification processes with neuro-fuzzy approaches may involve situations
where uncertainties arise, which may directly interfere with the quality of the results of the …

Interpretable machine learning is trending as it aims to build a human-understandable
decision process. There are two main types of machine learning systems: white-box and …

Evolving classifiers and especially evolving fuzzy classifiers have been established as a
prominent technique for addressing the recent demands in building classifiers in an …

Evolving fuzzy neural networks have the adaptive capacity to solve complex problems by
interpreting them. This is due to the fact that this type of approach provides valuable insights …

Fuzzy systems are the perfect systems for knowledge representation-the fuzzy rules on
which they are based can be interpreted and explained during the presentation of the …

In 2014, Hu introduced the concept of three-way decision spaces and axiomatic definition of
decision evaluation functions. In three-way decision spaces, decision evaluation function …