Simulated annealing: theory and applications
Simulated annealing: theory and applications
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
C4.5: programs for machine learning
C4.5: programs for machine learning
Construction of fuzzy classification systems with rectangular fuzzy rules using genetic algorithms
Fuzzy Sets and Systems - Special issue on fuzzy methods for computer vision and pattern recognition
Machine Learning
Induction of fuzzy decision trees
Fuzzy Sets and Systems
A fuzzy inductive learning strategy for modular rules
Fuzzy Sets and Systems
Generalized Version Space Learning Algorithm for Noisy and Uncertain Data
IEEE Transactions on Knowledge and Data Engineering
Machine Learning
Deriving Fuzzy Subsethood Measures from Violations of the Implication between Elements
IEA/AIE '98 Proceedings of the 11th international conference on Industrial and engineering applications of artificial intelligence and expert systems: methodology and tools in knowledge-based systems
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This paper proposes a simulated annealing-based approach for obtaining compact efficient classification systems from fuzzy data. Different methods for generating decision rules from fuzzy data share a problem in multidimensional spaces: their high cardinality. In order to solve it, the method of simulated annealing is proposed. This approach is illustrated with two well-known learning sets.