Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Uncertainty and vagueness in knowledge based systems
Uncertainty and vagueness in knowledge based systems
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Fuzzy neural networks: a survey
Fuzzy Sets and Systems
Neural networks in designing fuzzy systems for real world applications
Fuzzy Sets and Systems
Fuzzy Sets and Systems - Special issue on diagnostics and control through neural interpretations of fuzzy sets
Fuzzy Sets and Systems - Special issue on fuzzy neural control
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Constructing a fuzzy controller from data
Fuzzy Sets and Systems - Special issue on methods for data analysis in classificatin and control
The neural network model RuleNet and its application to mobile robot navigation
Fuzzy Sets and Systems - Special issue on methods for data analysis in classificatin and control
A neuro-fuzzy method to learn fuzzy classification rules from data
Fuzzy Sets and Systems - Special issue: application of neuro-fuzzy systems
Now comes the time to defuzzify neuro-fuzzy models
Fuzzy Sets and Systems - Special issue: fuzzy sets: where do we stand? Where do we go?
Generation and improvement of fuzzy classifiers with incremental learning using fuzzy RuleNet
SAC '95 Proceedings of the 1995 ACM symposium on Applied computing
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Foundations of Neuro-Fuzzy Systems
Foundations of Neuro-Fuzzy Systems
Foundations of Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Combining Classifiers of Pesticides Toxicity through a Neuro-fuzzy Approach
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
Evolving fuzzy classifiers using different model architectures
Fuzzy Sets and Systems
Measures of Ruleset Quality Capable to Represent Uncertain Validity
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Measures of ruleset quality for general rules extraction methods
International Journal of Approximate Reasoning
On-line evolving image classifiers and their application to surface inspection
Image and Vision Computing
SparseFIS: data-driven learning of fuzzy systems with sparsity constraints
IEEE Transactions on Fuzzy Systems
Fuzzy rule classifier: Capability for generalization in wood color recognition
Engineering Applications of Artificial Intelligence
Handling drifts and shifts in on-line data streams with evolving fuzzy systems
Applied Soft Computing
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Neuro-fuzzy classification systems offer a means of obtaining fuzzy classification rules by a learning algorithm. Although it is usually no problem to find a suitable fuzzy classifier by learning from data, it can, however, be hard to obtain a classifier that can be interpreted conveniently. There is usually a trade-off between accuracy and readability. This paper discusses NEFCLASS — a neuro-fuzzy approach for classification problems — and its implementation NEFCLASS-X. It is shown how a readable fuzzy classifier can be obtained by a learning process and how interactive strategies for pruning rules and variables from a trained classifier can enhance its interpretability.