Abstract
Genetic Programming (GP) may be used to model complex data but it must be “tuned” to get the best results. This process of tuning often gives insights into the data itself. This is discussed using examples from classification problems in molecular biology and the results and “rules of thumb” developed to tune the GP system are reviewed in light of current GP theory.
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MacLean, D., Wollesen, E.A., Worzel, B. (2005). Listening to Data: Tuning a Genetic Programming System. In: O’Reilly, UM., Yu, T., Riolo, R., Worzel, B. (eds) Genetic Programming Theory and Practice II. Genetic Programming, vol 8. Springer, Boston, MA. https://doi.org/10.1007/0-387-23254-0_15
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DOI: https://doi.org/10.1007/0-387-23254-0_15
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