C4.5: programs for machine learning
C4.5: programs for machine learning
General and Efficient Multisplitting of Numerical Attributes
Machine Learning
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Bounding the effect of noise in multiobjective learning classifier systems
Evolutionary Computation
Classification and Modeling with Linguistic Information Granules: Advanced Approaches to Linguistic Data Mining (Advanced Information Processing)
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Neural Networks
Dependence modeling rule mining using multi-objective genetic algorithms
AIA '08 Proceedings of the 26th IASTED International Conference on Artificial Intelligence and Applications
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In this paper, we show the usefulness of multiobjective genetic rule selection as a postprocessing procedure in data mining for pattern classification problems. First we extract a prespecified number of rules using a data mining technique. Then we apply multiobjective genetic rule selection to the extracted rules. Experimental results show that multiobjective genetic rule selection significantly decreases the number of extracted rules while improving their classification accuracy.