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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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(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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(Springer, 2011-04-27)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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(IEEE Press, 2010-07)A significant problem in the area of stock selection is that of identifying the factors that affect a security’s return. While modern portfolio theory suggests a linear multi-factor model in the form of Arbitrage Pricing ...
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(Springer, 2010-09)In this paper we investigate the profitability of evolved technical trading rules when controlling for data-mining bias. For the first time in the evolutionary computation literature, a comprehensive test for a rule’s ...
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(Springer, 2011)This Chapter examines cash dividends and share repurchases in the United States during the period 1990 to 2008. In the extant literature a variety of classical statistical methodologies have been adopted, foremost among ...
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(Springer, 2011-09)We present a novel visualisation method for island-based evolutionary algorithms based on the concept of tracers as adopted in medicine and molecular biology to follow a biochemical process. For example, a radioisotope or ...
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(Springer, 2011)This study evolves and categorises a population of conceptual designs by their ability to handle physical constraints. The design process involves a trade-off between form and function. The aesthetic considerations of the ...
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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 ...