CISUC - Balancing Learning and Overfitting in Genetic Programming with Interleaved Sampling of Training Data
CISUC

Balancing Learning and Overfitting in Genetic Programming with Interleaved Sampling of Training Data

Authors



Keywords

Genetic Programming, Overfitting, Generalization

Subject

Evolutionary Computation, Genetic Programming

Related Project

EnviGP - Improving Genetic Programming for the Environment and Other Applications

Conference

16th European Conference on Genetic Programming (EuroGP 2013), April 2013

PDF File

DOI


Cited by

Year 2015 : 4 citations

 Medernach, D., Fitzgerald, J., Azad, R., and Ryan, C.. "Wave: Incremental Erosion of Residual Error." Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference. ACM, 2015.

 Žegklitz, Jan, and Petr Pošík. "Model Selection and Overfitting in Genetic Programming: Empirical Study." Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference. ACM, 2015.

 Gonçalves, Eduardo C., Alexandre Plastino, and Alex A. Freitas. "Simpler is Better: a Novel Genetic Algorithm to Induce Compact Multi-label Chain Classifiers." Proceedings of the 2015 on Genetic and Evolutionary Computation Conference. ACM, 2015.

 Žegklitz, Jan, and Petr Pošík. "Model Selection and Overfitting in Genetic Programming: Empirical Study." arXiv preprint arXiv:1504.08168 (2015).

Year 2014 : 5 citations

 Fitzgerald, Jeannie. "Bias and Variance Reduction Strategies for Improving Generalisation Performance of Genetic Programming on Binary Classification Tasks." PhD diss., University of Limerick, 2014.

 Azad, R., David Medernach, and Conor Ryan. "Efficient interleaved sampling of training data in genetic programming." In Proceedings of the 2014 conference companion on Genetic and evolutionary computation companion, pp. 127-128. ACM, 2014.

 Muhammad Atif Azad, R., David Medernach, and Conor Ryan. "Efficient approaches to interleaved sampling of training data for symbolic regression." In Nature and Biologically Inspired Computing (NaBIC), 2014 Sixth World Congress on, pp. 176-183. IEEE, 2014.

 Goldstein, Evan B., and Giovanni Coco. "A machine learning approach for the prediction of settling velocity." Water Resources Research (2014).

 Martínez, Yuliana, Leonardo Trujillo, Enrique Naredo, and Pierrick Legrand. "A Comparison of Fitness-Case Sampling Methods for Symbolic Regression with Genetic Programming." EVOLVE-A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V (2014): 201-212.

Year 2013 : 2 citations

 Gonçalves, Eduardo Corrêa, Alexandre Plastino, and Alex A. Freitas. "A Genetic Algorithm for Optimizing the Label Ordering in Multi-Label Classifier Chains." Proceedings of the 2013 25th IEEE International Conference on Tools with Artificial Intelligence (ICTAI). IEEE Computer Society Conference Publishing Services (CPS), 2013.

 Goldstein, E. B., G. Coco, A. B. Murray, and M. O. Green. "Data driven components in a model of inner shelf sorted bedforms: a new hybrid model." Earth Surface Dynamics Discussions 1, no. 1 (2013): 531-569.