Neural networks for pattern recognition
Neural networks for pattern recognition
Machine Learning
Neural Networks: Tricks of the Trade, this book is an outgrowth of a 1996 NIPS workshop
Generalization Performance of Overtrained Back-Propagation Networks
Proceedings of the EURASIP Workshop 1990 on Neural Networks
Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language
Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)
Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)
GEVA: grammatical evolution in Java
ACM SIGEVOlution
Foundations in Grammatical Evolution for Dynamic Environments
Foundations in Grammatical Evolution for Dynamic Environments
Grammar-based Genetic Programming: a survey
Genetic Programming and Evolvable Machines
Open issues in genetic programming
Genetic Programming and Evolvable Machines
Natural Computing in Computational Finance
Natural Computing in Computational Finance
Early stopping criteria to counteract overfitting in genetic programming
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Validation sets for evolutionary curtailment with improved generalisation
ICHIT'11 Proceedings of the 5th international conference on Convergence and hybrid information technology
Evolving interpolating models of net ecosystem CO2 exchange using grammatical evolution
EuroGP'12 Proceedings of the 15th European conference on Genetic Programming
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
On the utility of trading criteria based retraining in forex markets
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
Robust estimation of vector autoregression (VAR) models using genetic algorithms
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
On the impact of streaming interface heuristics on GP trading agents: an FX benchmarking study
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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This paper investigates the effects of early stopping as a method to counteract overfitting in evolutionary data modelling using Genetic Programming. Early stopping has been proposed as a method to avoid model overtraining, which has been shown to lead to a significant degradation of out-of-sample performance. If we assume some sort of performance metric maximisation, the most widely used early training stopping criterion is the moment within the learning process that an unbiased estimate of the performance of the model begins to decrease after a strictly monotonic increase through the earlier learning iterations. We are conducting an initial investigation on the effects of early stopping in the performance of Genetic Programming in symbolic regression and financial modelling. Empirical results suggest that early stopping using the above criterion increases the extrapolation abilities of symbolic regression models, but is by no means the optimal training-stopping criterion in the case of a real-world financial dataset.