Cellular automata machines: a new environment for modeling
Cellular automata machines: a new environment for modeling
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
C4.5: programs for machine learning
C4.5: programs for machine learning
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
Machine Learning
An Information Theoretic Approach to Rule Induction from Databases
IEEE Transactions on Knowledge and Data Engineering
Machine Learning
Inductive Genetic Programming with Decision Trees
ECML '97 Proceedings of the 9th European Conference on Machine Learning
Genetic Programming for Feature Discovery and Image Discrimination
Proceedings of the 5th International Conference on Genetic Algorithms
CAGE: A Tool for Parallel Genetic Programming Applications
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Metadata and its impact on libraries: Book Reviews
Journal of the American Society for Information Science and Technology
An Optimal Constrained Pruning Strategy for Decision Trees
INFORMS Journal on Computing
Maximum margin decision surfaces for increased generalisation in evolutionary decision tree learning
EuroGP'11 Proceedings of the 14th European conference on Genetic programming
Information Sciences: an International Journal
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A parallel genetic programming approach to induce decision trees in large data sets is presented. A population of trees is evolved by employing the genetic operators and every individual is evaluated by using a fitness function based on the J-measure. The method is able to deal with large data sets since it uses a parallel implementation of genetic programming through the grid model. Experiments on data sets from the UCI machine learning repository show better results with respect to C5. Furthermore, performance results show a nearly linear speedup.