Validation sets, genetic programming and generalisation

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Abstract

This paper investigates a new application of a validation set when using a three data set methodology with Genetic Programming (GP). Our system uses Validation Pressure combined with Validation Elitism to influence fitness evaluation and population structure with the aim of improving the system's ability to evolve individuals with an enhanced capacity for generalisation. This strategy facilitates the use of a validation set to reduce over-fitting while mitigating the loss of training data associated with traditional methods employing a validation set. The method is tested on five benchmark binary classification data sets and results obtained suggest that the strategy can deliver improved generalisation on unseen test data. © Springer-Verlag London Limited 2011.

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APA

Fitzgerald, J., & Ryan, C. (2011). Validation sets, genetic programming and generalisation. In Res. and Dev. in Intelligent Syst. XXVIII: Incorporating Applications and Innovations in Intel. Sys. XIX - AI 2011, 31st SGAI Int. Conf. on Innovative Techniques and Applications of Artificial Intel. (pp. 79–92). Springer London. https://doi.org/10.1007/978-1-4471-2318-7_6

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