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Search Results for Collection: Financial Mathematics Computation Cluster
Now showing items 1-7 of 7
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(Springer, 2011-04)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, ...
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(ACM, 2011)Early stopping typically stops training the first time validation fitness disimproves. This may not be the best strategy given that validation fitness can subsequently increase or decrease. We examine the effects of stopping ...
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(Springer, 2011-04)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, ...
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Maximum margin decision surfaces for increased generalisation in evolutionary decision tree learning (Springer, 2011-04-27)Decision tree learning is one of the most widely used and practical methods for inductive inference. We present a novel method that increases the generalisation of genetically-induced classification trees, which employ ...
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(Springer, 2012)The last ten years has seen the introduction and rapid growth of a market in weather derivatives, financial instruments whose payoffs are determined by the outcome of an underlying weather metric. These instruments allow ...
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(IEEE Press, 2010-07)Designing a suitable objective function is an essential step in successfully applying an evolutionary algorithm to a problem. In this study we apply a grammar-based Genetic Programming algorithm called Grammatical Evolution ...
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(Springer, 2011)This chapter explores the issue of overfitting in grammar-based Genetic Programming. Tools such as Genetic Programming are well suited to problems in finance where we seek to learn or induce a model from data. Models that ...
Now showing items 1-7 of 7