Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
C4.5: programs for machine learning
C4.5: programs for machine learning
A neuro-fuzzy method to learn fuzzy classification rules from data
Fuzzy Sets and Systems - Special issue: application of neuro-fuzzy systems
Fuzzy Sets and Systems - Special issue on clustering and learning
Learning feed-forward and recurrent fuzzy systems: a genetic approach
Journal of Systems Architecture: the EUROMICRO Journal - Special issue on evolutionary computing
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
Artficial Immune Systems and Their Applications
Artficial Immune Systems and Their Applications
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Immunocomputing: Principles and Applications
Immunocomputing: Principles and Applications
Finding useful fuzzy concepts for pattern classification using genetic algorithm
Information Sciences: an International Journal
Hybrid learning models to get the interpretability–accuracy trade-off in fuzzy modeling
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Thalassaemia classification by neural networks and genetic programming
Information Sciences: an International Journal
Fuzzy integral-based perceptron for two-class pattern classification problems
Information Sciences: an International Journal
Weighting fuzzy classification rules using receiver operating characteristics (ROC) analysis
Information Sciences: an International Journal
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
A comparison of classification accuracy of four genetic programming-evolved intelligent structures
Information Sciences: an International Journal
Similarity measures in fuzzy rule base simplification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A fuzzy classifier with ellipsoidal regions
IEEE Transactions on Fuzzy Systems
Implementation of evolutionary fuzzy systems
IEEE Transactions on Fuzzy Systems
GA-fuzzy modeling and classification: complexity and performance
IEEE Transactions on Fuzzy Systems
Compact and transparent fuzzy models and classifiers through iterative complexity reduction
IEEE Transactions on Fuzzy Systems
Neuro-fuzzy rule generation: survey in soft computing framework
IEEE Transactions on Neural Networks
An antibody network inspired evolutionary framework for distributed object computing
Information Sciences: an International Journal
Information Sciences: an International Journal
A hybrid coevolutionary algorithm for designing fuzzy classifiers
Information Sciences: an International Journal
On a reflexivity-preserving family of cardinality-based fuzzy comparison measures
Information Sciences: an International Journal
An immune inspired co-evolutionary affinity network for prefetching of distributed object
Journal of Parallel and Distributed Computing
Information Sciences: an International Journal
Information Sciences: an International Journal
So near and yet so far: New insight into properties of some well-known classifier paradigms
Information Sciences: an International Journal
Mining fuzzy rules using an Artificial Immune System with fuzzy partition learning
Applied Soft Computing
Artificial immune multi-objective SAR image segmentation with fused complementary features
Information Sciences: an International Journal
Structural design of the danger model immune algorithm
Information Sciences: an International Journal
A hybrid fuzzy rule-based multi-criteria framework for sustainable project portfolio selection
Information Sciences: an International Journal
Information Sciences: an International Journal
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This paper proposed an algorithm to design a fuzzy classification system based on immune principles. The proposed algorithm evolves a population of antibodies based on the clonal selection and hypermutation principles. The membership function parameters and the fuzzy rule set including the number of rules inside it are evolved at the same time. Each antibody (candidate solution) corresponds to a fuzzy classification rule set. We compared our algorithm with other classification schemes on some benchmark datasets. The results demonstrated the effectiveness of the proposed immune algorithm.