Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Using Genetic Algorithms for Concept Learning
Machine Learning - Special issue on genetic algorithms
Competition-Based Induction of Decision Models from Examples
Machine Learning - Special issue on genetic algorithms
Mining quantitative association rules in large relational tables
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
An evolutionary algorithm to discover numeric association rules
Proceedings of the 2002 ACM symposium on Applied computing
Genetic Algorithms for Machine Learning
Genetic Algorithms for Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms for Pattern Recognition
Genetic Algorithms for Pattern Recognition
Data Mining Using Grammar-Based Genetic Programming and Applications
Data Mining Using Grammar-Based Genetic Programming and Applications
Data Mining and Knowledge Discovery with Evolutionary Algorithms
Data Mining and Knowledge Discovery with Evolutionary Algorithms
Discretization: An Enabling Technique
Data Mining and Knowledge Discovery
Scalable Algorithms for Association Mining
IEEE Transactions on Knowledge and Data Engineering
SIA: A Supervised Inductive Algorithm with Genetic Search for Learning Attributes based Concepts
ECML '93 Proceedings of the European Conference on Machine Learning
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Discovering Numeric Association Rules via Evolutionary Algorithm
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
A learning system based on genetic adaptive algorithms
A learning system based on genetic adaptive algorithms
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Strength or Accuracy: Credit Assignment in Learning Classifier Systems
Strength or Accuracy: Credit Assignment in Learning Classifier Systems
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
A trie-based APRIORI implementation for mining frequent item sequences
Proceedings of the 1st international workshop on open source data mining: frequent pattern mining implementations
Computers and Operations Research
Evolutionary Computation in Data Mining (Studies in Fuzziness and Soft Computing)
Evolutionary Computation in Data Mining (Studies in Fuzziness and Soft Computing)
A Hellinger-based discretization method for numeric attributes in classification learning
Knowledge-Based Systems
A discretization algorithm based on Class-Attribute Contingency Coefficient
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
A genetic-fuzzy mining approach for items with multiple minimum supports
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Genetic Fuzzy Systems: Recent Developments and Future Directions; Guest editors: Jorge Casillas, Brian Carse
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Improving the performance of a pittsburgh learning classifier system using a default rule
IWLCS'03-05 Proceedings of the 2003-2005 international conference on Learning classifier systems
Association rule mining: models and algorithms
Association rule mining: models and algorithms
Genetic-Fuzzy Data Mining With Divide-and-Conquer Strategy
IEEE Transactions on Evolutionary Computation
Finding association rules in semantic web data
Knowledge-Based Systems
Expert Systems with Applications: An International Journal
Discovering gene association networks by multi-objective evolutionary quantitative association rules
Journal of Computer and System Sciences
Web usage mining with evolutionary extraction of temporal fuzzy association rules
Knowledge-Based Systems
QAR-CIP-NSGA-II: A new multi-objective evolutionary algorithm to mine quantitative association rules
Information Sciences: an International Journal
QuantMiner for mining quantitative association rules
The Journal of Machine Learning Research
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DataMining is most commonly used in attempts to induce association rules from transaction data which can help decision-makers easily analyze the data and make good decisions regarding the domains concerned. Most conventional studies are focused on binary or discrete-valued transaction data, however the data in real-world applications usually consists of quantitative values. In the last years, many researches have proposed Genetic Algorithms for mining interesting association rules from quantitative data. In this paper, we present a study of three genetic association rules extraction methods to show their effectiveness for mining quantitative association rules. Experimental results over two real-world databases are showed.