Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
Explora: a multipattern and multistrategy discovery assistant
Advances in knowledge discovery and data mining
Fast discovery of association rules
Advances in knowledge discovery and data mining
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Data Mining Using Grammar-Based Genetic Programming and Applications
Data Mining Using Grammar-Based Genetic Programming and Applications
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
An Algorithm for Multi-relational Discovery of Subgroups
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Rule Evaluation Measures: A Unifying View
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
Subgroup Discovery with CN2-SD
The Journal of Machine Learning Research
Multi-objective rule mining using genetic algorithms
Information Sciences: an International Journal - Special issue: Soft computing data mining
Expert-guided subgroup discovery: methodology and application
Journal of Artificial Intelligence Research
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Making CN2-SD subgroup discovery algorithm scalable to large size data sets using instance selection
Expert Systems with Applications: An International Journal
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Dependence modeling rule mining using multi-objective genetic algorithms
AIA '08 Proceedings of the 26th IASTED International Conference on Artificial Intelligence and Applications
IEEE Transactions on Fuzzy Systems
A multi-objective evolutionary approach for subgroup discovery
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
Evolutionary multi objective optimization for rule mining: a review
Artificial Intelligence Review
Expert Systems with Applications: An International Journal
Hi-index | 0.00 |
This paper presents a multiobjective genetic algorithm which obtains fuzzy rules for subgroup discovery in disjunctive normal form. This kind of fuzzy rules lets us represent knowledge about patterns of interest in an explanatory and understandable form which can be used by the expert. The evolutionary algorithm follows a multiobjective approach in order to optimize in a suitable way the different quality measures used in this kind of problems. Experimental evaluation of the algorithm, applying it to a market problem studied in the University of Mondragón (Spain), shows the validity of the proposal. The application of the proposal to this problem allows us to obtain novel and valuable knowledge for the experts.