Parallel computing (2nd ed.): theory and practice
Parallel computing (2nd ed.): theory and practice
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
Knowledge-based artificial neural networks
Artificial Intelligence
Limitations of cycle stealing for parallel processing on a network of homogeneous workstations
Journal of Parallel and Distributed Computing
Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Mining Very Large Databases with Parallel Processing
Mining Very Large Databases with Parallel Processing
When Does Overfitting Decrease Prediction Accuracy in Induced Decision Trees and Rule Sets?
EWSL '91 Proceedings of the European Working Session on Machine Learning
SIA: A Supervised Inductive Algorithm with Genetic Search for Learning Attributes based Concepts
ECML '93 Proceedings of the European Conference on Machine Learning
A Quantitative Study of Small Disjuncts
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
A learning system based on genetic adaptive algorithms
A learning system based on genetic adaptive algorithms
Biostatistical Analysis (5th Edition)
Biostatistical Analysis (5th Edition)
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Search-intensive concept induction
Evolutionary Computation
Handbook of Parametric and Nonparametric Statistical Procedures
Handbook of Parametric and Nonparametric Statistical Procedures
Soft Computing - A Fusion of Foundations, Methodologies and Applications
NOW G-Net: learning classification programs on networks ofworkstations
IEEE Transactions on Evolutionary Computation
Rule induction based-on coevolutionary algorithms for image annotation
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
Science of Computer Programming
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This paper presents an Efficient Distributed Genetic Algorithm for classification Rule extraction in data mining (EDGAR), which promotes a new method of data distribution in computer networks. This is done by spatial partitioning of the population into several semi-isolated nodes, each evolving in parallel and possibly exploring different regions of the search space. The presented algorithm shows some advantages when compared with other distributed algorithms proposed in the specific literature. In this way, some results are presented showing significant learning rate speedup without compromising the accuracy.