Induction of ripple-down rules applied to modeling large databases
Journal of Intelligent Information Systems
Generating Accurate Rule Sets Without Global Optimization
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Particle swarm based Data Mining Algorithms for classification tasks
Parallel Computing - Special issue: Parallel and nature-inspired computational paradigms and applications
A Novel Multiobjective Particle Swarm Optimization for Buoys-Arrangement Design
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
A critical review of multi-objective optimization in data mining: a position paper
ACM SIGKDD Explorations Newsletter
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Particle Swarm Algorithm for Classification Rules Generation
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 02
HIS '06 Proceedings of the Sixth International Conference on Hybrid Intelligent Systems
A hybrid system for multiobjective problems - A case study in NP-hard problems
Knowledge-Based Systems
Intelligent multiobjective particle swarm optimization based on AER model
EPIA'05 Proceedings of the 12th Portuguese conference on Progress in Artificial Intelligence
A MOPSO algorithm based exclusively on pareto dominance concepts
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Mining classification rules using evolutionary multi-objective algorithms
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Evolutionary multi-objective optimization: a historical view of the field
IEEE Computational Intelligence Magazine
A hybrid particle swarm optimization approach for clustering and classification of datasets
Knowledge-Based Systems
An experimental ant colony approach for the geolocation of verbal route descriptions
Knowledge-Based Systems
The agile improvement of MMORPGs based on the enhanced chaotic neural network
Knowledge-Based Systems
ACROA: Artificial Chemical Reaction Optimization Algorithm for global optimization
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Multi-objective hybrid evolutionary algorithms for radial basis function neural network design
Knowledge-Based Systems
Novel swarm optimization for mining classification rules on thyroid gland data
Information Sciences: an International Journal
WSEAS Transactions on Information Science and Applications
Game team balancing by using particle swarm optimization
Knowledge-Based Systems
Computers & Mathematics with Applications
International Journal of Applied Metaheuristic Computing
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In this paper, classification rule mining which is one of the most studied tasks in data mining community has been modeled as a multi-objective optimization problem with predictive accuracy and comprehensibility objectives. A multi-objective chaotic particle swarm optimization (PSO) method has been introduced as a search strategy to mine classification rules within datasets. The used extension to PSO uses similarity measure for neighborhood and far-neighborhood search to store the global best particles found in multi-objective manner. For the bi-objective problem of rule mining of high accuracy/comprehensibility, the multi-objective approach is intended to allow the PSO algorithm to return an approximation to the upper accuracy/comprehensibility border, containing solutions that are spread across the border. The experimental results show the efficiency of the algorithm.