An Optimal Constrained Pruning Strategy for Decision Trees
INFORMS Journal on Computing
Ensemble techniques for parallel genetic programming based classifiers
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Information Sciences: an International Journal
Hi-index | 0.00 |
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 and an out of core technique for those data sets that do not fit in main memory.Preliminary experiments on data sets from the UCI machine learning repository give good classification outcomes and assess the scalability of the method.