This paper investigates a new application of a validation set when using a three data set methodology with Genetic Programming (GP). Our system uses
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.