Titlebook: Genetic Programming Theory and Practice XII; Rick Riolo,William P. Worzel,Mark Kotanchek Book 2015 Springer International Publishing Switz

Inflated

Sequential Symbolic Regression with Genetic Programming,cantly outperforms SGP and presents no statistical difference from GP. More importantly, they show the potential of the proposed approach: an effective way of applying geometric semantic operators to combine different (partial) solutions, and at the same time, avoiding the exponential growth problem

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Extremely Accurate Symbolic Regression for Large Feature Problems,etail. This algorithm was extremely accurate, on a single processor, for up to 25 features (columns); and, a cloud configuration was used to extend the extreme accuracy up to as many as 100 features..While the previous algorithm’s extreme accuracy for deep problems with a small number of features (2

paroxysm

How to Exploit Alignment in the Error Space: Two Different GP Models,andard GP and geometric semantic GP on two complex real-life applications. At the same time, a preliminary set of results obtained on a set of symbolic regression benchmarks indicate that POGP, although rather new and still in need of improvement, is a very promising model, that deserves future deve

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Nebulous

Stagger

https://doi.org/10.1007/978-3-658-23240-5cantly outperforms SGP and presents no statistical difference from GP. More importantly, they show the potential of the proposed approach: an effective way of applying geometric semantic operators to combine different (partial) solutions, and at the same time, avoiding the exponential growth problem

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Suppository

https://doi.org/10.1007/978-3-658-11655-2andard GP and geometric semantic GP on two complex real-life applications. At the same time, a preliminary set of results obtained on a set of symbolic regression benchmarks indicate that POGP, although rather new and still in need of improvement, is a very promising model, that deserves future deve

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角斗士

,Identification of Novel Genetic Models of Glaucoma Using the “EMERGENT” Genetic Programming-Based Auence risk in the context of our local ecology. The complexity of the genotype to phenotype mapping relationship for common diseases like POAG necessitates analytical approaches that move beyond parametric statistical methods such as logistic regression that assume a particular mathematical model. T