Can approximate reasoning be consistent?
Fuzzy Sets and Systems
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Fuzzy model identification: selected approaches
Fuzzy model identification: selected approaches
Minimum description length analysis
The handbook of brain theory and neural networks
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IEEE Software
Accuracy Improvements in Linguistic Fuzzy Modeling
Accuracy Improvements in Linguistic Fuzzy Modeling
Generating English summaries of time series data using the Gricean maxims
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Hybrid learning models to get the interpretability–accuracy trade-off in fuzzy modeling
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Preface: Special Issue on Genetic Fuzzy Systems and the Interpretability--Accuracy Trade-off
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
Application of Fuzzy Logic to Approximate Reasoning Using Linguistic Synthesis
IEEE Transactions on Computers
International Journal of Intelligent Systems
Interpretability constraints for fuzzy information granulation
Information Sciences: an International Journal
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Genetic Fuzzy Systems: Recent Developments and Future Directions; Guest editors: Jorge Casillas, Brian Carse
IEEE Transactions on Knowledge and Data Engineering
Introduction to Mathematical Logic
Introduction to Mathematical Logic
Practical inference with systems of gradual implicative rules
IEEE Transactions on Fuzzy Systems
Similarity measures in fuzzy rule base simplification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On generating FC3 fuzzy rule systems from data usingevolution strategies
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Improving the interpretability of TSK fuzzy models by combining global learning and local learning
IEEE Transactions on Fuzzy Systems
Constructing fuzzy models with linguistic integrity from numerical data-AFRELI algorithm
IEEE Transactions on Fuzzy Systems
Incorporation, characterization, and conversion of negative rules into fuzzy inference systems
IEEE Transactions on Fuzzy Systems
Designing fuzzy inference systems from data: An interpretability-oriented review
IEEE Transactions on Fuzzy Systems
Generating an interpretable family of fuzzy partitions from data
IEEE Transactions on Fuzzy Systems
Why the magic number seven plus or minus two
Mathematical and Computer Modelling: An International Journal
IEEE Transactions on Fuzzy Systems - Special section on computing with words
On reducing computational overhead in multi-objective genetic Takagi-Sugeno fuzzy systems
Applied Soft Computing
Interpretability assessment of fuzzy knowledge bases: A cointension based approach
International Journal of Approximate Reasoning
Intelligent data analysis and model interpretation with spectral analysis fuzzy symbolic modeling
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
Identification of transparent, compact, accurate and reliable linguistic fuzzy models
Information Sciences: an International Journal
Interpretability of linguistic fuzzy rule-based systems: An overview of interpretability measures
Information Sciences: an International Journal
Editorial: Special issue on interpretable fuzzy systems
Information Sciences: an International Journal
Design of fuzzy rule-based classifiers with semantic cointension
Information Sciences: an International Journal
On-line valuation of residential premises with evolving fuzzy models
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part I
Multi-objective evolutionary fuzzy systems
WILF'11 Proceedings of the 9th international conference on Fuzzy logic and applications
A double axis classification of interpretability measures for linguistic fuzzy rule-based systems
WILF'11 Proceedings of the 9th international conference on Fuzzy logic and applications
Investigation of evolving fuzzy systems methods FLEXFIS and eTS on predicting residential prices
WILF'11 Proceedings of the 9th international conference on Fuzzy logic and applications
Expert Systems with Applications: An International Journal
On employing fuzzy modeling algorithms for the valuation of residential premises
Information Sciences: an International Journal
A hybrid fuzzy rule-based multi-criteria framework for sustainable project portfolio selection
Information Sciences: an International Journal
An attempt to employ genetic fuzzy systems to predict from a data stream of premises transactions
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
Information Sciences: an International Journal
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
An efficient multi-objective evolutionary fuzzy system for regression problems
International Journal of Approximate Reasoning
Adaptability, interpretability and rule weights in fuzzy rule-based systems
Information Sciences: an International Journal
A fuzzy system index to preserve interpretability in deep tuning of fuzzy rule based classifiers
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Interpretability is acknowledged as the main advantage of fuzzy systems and it should be given a main role in fuzzy modeling. Classical systems are viewed as black boxes because mathematical formulas set the mapping between inputs and outputs. On the contrary, fuzzy systems (if they are built regarding some constraints) can be seen as gray boxes in the sense that every element of the whole system can be checked and understood by a human being. Interpretability is essential for those applications with high human interaction, for instance decision support systems in fields like medicine, economics, etc. Since interpretability is not guaranteed by definition, a huge effort has been done to find out the basic constraints to be superimposed during the fuzzy modeling process. People talk a lot about interpretability but the real meaning is not clear. Understanding of fuzzy systems is a subjective task which strongly depends on the background (experience, preferences, and knowledge) of the person who makes the assessment. As a consequence, although there have been a few attempts to define interpretability indices, there is still not a universal index widely accepted. As part of this work, with the aim of evaluating the most used indices, an experimental analysis (in the form of a web poll) was carried out yielding some useful clues to keep in mind regarding interpretability assessment. Results extracted from the poll show the inherent subjectivity of the measure because we collected a huge diversity of answers completely different at first glance. However, it was possible to find out some interesting user profiles after comparing carefully all the answers. It can be concluded that defining a numerical index is not enough to get a widely accepted index. Moreover, it is necessary to define a fuzzy index easily adaptable to the context of each problem as well as to the user quality criteria.