An Empirical Study of Multipopulation Genetic Programming
Genetic Programming and Evolvable Machines
Lexicographic Parsimony Pressure
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Modification point depth and genome growth in genetic programming
Evolutionary Computation
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Genetic programming for computational pharmacokinetics in drug discovery and development
Genetic Programming and Evolvable Machines
The impact of population size on code growth in GP: analysis and empirical validation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Genetic Programming and Evolvable Machines
Extending Operator Equalisation: Fitness Based Self Adaptive Length Distribution for Bloat Free GP
EuroGP '09 Proceedings of the 12th European Conference on Genetic Programming
Operator equalisation, bloat and overfitting: a study on human oral bioavailability prediction
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Dynamic maximum tree depth: a simple technique for avoiding bloat in tree-based GP
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
EvoBIO'07 Proceedings of the 5th European conference on Evolutionary computation, machine learning and data mining in bioinformatics
Fitness distance correlation in structural mutation genetic programming
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
On the limiting distribution of program sizes in tree-based genetic programming
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Operator equalisation and bloat free GP
EuroGP'08 Proceedings of the 11th European conference on Genetic programming
Crossover, sampling, bloat and the harmful effects of size limits
EuroGP'08 Proceedings of the 11th European conference on Genetic programming
A Field Guide to Genetic Programming
A Field Guide to Genetic Programming
Reassembling operator equalisation: a secret revealed
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A quantitative study of learning and generalization in genetic programming
EuroGP'11 Proceedings of the 14th European conference on Genetic programming
Reassembling operator equalisation: a secret revealed
ACM SIGEVOlution
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Random sampling technique for overfitting control in genetic programming
EuroGP'12 Proceedings of the 15th European conference on Genetic Programming
Operator equalisation for bloat free genetic programming and a survey of bloat control methods
Genetic Programming and Evolvable Machines
Balancing learning and overfitting in genetic programming with interleaved sampling of training data
EuroGP'13 Proceedings of the 16th European conference on Genetic Programming
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Predicting the toxicity of new potential drugs is a fundamental step in the drug design process. Recent contributions have shown that, even though Genetic Programming is a promising method for this task, the problem of predicting the toxicity of molecular compounds is complex and difficult to solve. In particular, when executed for predicting drug toxicity, Genetic Programming undergoes the well-known phenomenon of bloat, i.e. the growth in code size during the evolutionary process without a corresponding improvement in fitness. We hypothesize that this might cause overfitting and thus prevent the method from discovering simpler and potentially more general solutions. For this reason, in this paper we investigate two recently defined variants of the operator equalization bloat control method for Genetic Programming. We show that these two methods are bloat free also when executed on this complex problem. Nevertheless, overfitting still remains an issue. Thus, contradicting the generalized idea that bloat and overfitting are strongly related, we argue that the two phenomena are independent from each other and that eliminating bloat does not necessarily eliminate overfitting.