Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Machine Learning
Learning fuzzy classification rules from labeled data
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on recent advances in soft computing
An introduction to variable and feature selection
The Journal of Machine Learning Research
Intelligent Sensory Evaluation: Methodologies and Applications
Intelligent Sensory Evaluation: Methodologies and Applications
International Journal of Intelligent Systems
Interpretability constraints for fuzzy information granulation
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Practical inference with systems of gradual implicative rules
IEEE Transactions on Fuzzy Systems
A framework for reasoning with soft information
Information Sciences: an International Journal
Why fuzzy decision trees are good rankers
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems - Special section on computing with words
Semantic constraints for membership function optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Designing fuzzy inference systems from data: An interpretability-oriented review
IEEE Transactions on Fuzzy Systems
Fuzzy basis functions, universal approximation, and orthogonal least-squares learning
IEEE Transactions on Neural Networks
Generating understandable and accurate fuzzy rule-based systems in a java environment
WILF'11 Proceedings of the 9th international conference on Fuzzy logic and applications
Expert Systems with Applications: An International Journal
Generation of a probabilistic fuzzy rule base by learning from examples
Information Sciences: an International Journal
An iterative approach to build relevant ontology-aware data-driven models
Information Sciences: an International Journal
Information Sciences: an International Journal
Fuzzy partitions: A way to integrate expert knowledge into distance calculations
Information Sciences: an International Journal
Computers and Electronics in Agriculture
Adaptability, interpretability and rule weights in fuzzy rule-based systems
Information Sciences: an International Journal
Statistical analysis of parametric t-norms
Information Sciences: an International Journal
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Fuzzy inference systems (FIS) are likely to play a significant part in system modeling, provided that they remain interpretable following learning from data. The aim of this paper is to set up some guidelines for interpretable FIS learning, based on practical experience with fuzzy modeling in various fields. An open source software system called FisPro has been specifically designed to provide generic tools for interpretable FIS design and learning. It can then be extended with the addition of new contributions. This work presents a global approach to design data-driven FIS that satisfy certain interpretability and accuracy criteria. It includes fuzzy partition generation, rule learning, input space reduction and rule base simplification. The FisPro implementation is discussed and illustrated through several detailed case studies.