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Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Backward-chaining evolutionary algorithms
Artificial Intelligence
Data Mining with Decision Trees: Theroy and Applications
Data Mining with Decision Trees: Theroy and Applications
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
Evolving computer programs without subtree crossover
IEEE Transactions on Evolutionary Computation
Diversity in genetic programming: an analysis of measures and correlation with fitness
IEEE Transactions on Evolutionary Computation
Controlling overfitting in symbolic regression based on a bias/variance error decomposition
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
Adaptive distance metrics for nearest neighbour classification based on genetic programming
EuroGP'13 Proceedings of the 16th European conference on Genetic Programming
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In this paper, an investigation of evolvable probabilistic classifiers is conducted, along with a thorough comparison between a classical Gaussian distance model, and the induction of Gaussian-to-circle projection model. The newly introduced model refers to a distance fitness measure, based on the projection of Gaussian distributions with geometric circles. The projection architecture aims to model and classify physical aggressive behaviours, by using biomechanical primitives. The primitives are being used to model the dynamics of the aggressive activities, by evolving biomechanical classifiers, which can discriminate between three behaviours and six actions. Both evolutionary models have shown strong discrimination performances on recognising the individual actions of each behaviour. From the comparison, the proposed model outperformed the classical one with three ensemble programs.