SIA: A Supervised Inductive Algorithm with Genetic Search for Learning Attributes based Concepts
ECML '93 Proceedings of the European Conference on Machine Learning
Using GPUs for Machine Learning Algorithms
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Fast rule matching for learning classifier systems via vector instructions
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Classifier fitness based on accuracy
Evolutionary Computation
An analysis of matching in learning classifier systems
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Fast support vector machine training and classification on graphics processors
Proceedings of the 25th international conference on Machine learning
GP on SPMD parallel graphics hardware for mega Bioinformatics data mining
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue (1143 - 1198) " Distributed Bioinspired Algorithms"; Guest editors: F. Fernández de Vega, E. Cantú-Paz
A mixed discrete-continuous attribute list representation for large scale classification domains
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
A population-based approach to finding the matchset of a learning classifier system efficiently
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Coarse grain parallelization of evolutionary algorithms on GPGPU cards with EASEA
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Effect of the block occupancy in GPGPU over the performance of particle swarm algorithm
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part I
Fast prediction computation in learning classifier systems using CUDA
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Automatically defined functions for learning classifier systems
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Estimation of distribution algorithms: from available implementations to potential developments
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Large scale data mining using genetics-based machine learning
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
GPU-Based evaluation to accelerate particle swarm algorithm
EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part I
Post-processing operators for decision lists
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Large scale data mining using genetics-based machine learning
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
On GPU based fitness evaluation with decoupled training partition cardinality
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
pEvoSAT: a novel permutation based genetic algorithm for solving the boolean satisfiability problem
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Large scale data mining using genetics-based machine learning
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Efficient training set use for blood pressure prediction in a large scale learning classifier system
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Parallel multi-objective Ant Programming for classification using GPUs
Journal of Parallel and Distributed Computing
High performance evaluation of evolutionary-mined association rules on GPUs
The Journal of Supercomputing
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In this paper we introduce a method for computing fitness in evolutionary learning systems based on NVIDIA's massive parallel technology using the CUDA library. Both the match process of a population of classifiers against a training set and the computation of the fitness of each classifier from its matches have been parallelized. This method has been integrated within the BioHEL evolutionary learning system. The methodology presented in this paper can be easily extended to any evolutionary learning system. The method has been tested using a broad set of problems with varying number of attributes and instances. The evaluation function by itself achieves speedups up to 52.4X while its integration with the entire learning process achieves speedups up to 58.1X. Moreover, the speedup increases when the CUDA-based fitness computation is combined with other efficiency enhancement mechanisms.