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Evolving Simple Symbolic Regression Models by Multi-Objective Genetic Programming Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Prime-Time: Symbolic Regression Takes Its Place in the Real World

Authors : Sean Stijven, Ekaterina Vladislavleva, Arthur Kordon, Lander Willem, Mark E. Kotanchek

Published in: Genetic Programming Theory and Practice XIII

Publisher: Springer International Publishing

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Abstract

In this chapter we review a number of real-world applications where symbolic regression was used recently and with great success. Industrial scale symbolic regression armed with the power to select right variables and variable combinations, build robust trustable predictions and guide experimentation has undoubtedly earned its place in industrial process optimization, business forecasting, product design and now complex systems modeling and policy making.

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previous chapter Multiclass Classification Through Multidimensional Clustering
Footnotes
1
Attack rate is defined as a ratio of the new cases in the population at risk to the total size of the population at risk.
 
Literature
Andradóttir S, Chiu W, Goldsman D, Lee M, Tsui K, Sander B, Fisman D, Nizam A (2011) Reactive strategies for containing developing outbreaks of pandemic influenza. BMC Public Health 11(Suppl 1):S1CrossRef
Chao D, Halloran M, Obenchain V, Longini I (2010) FluTE, a publicly available stochastic influenza epidemic simulation model. PLoS Comput Biol 6(1):e1000,656MathSciNetCrossRef
Crombecq K (2011) Surrogate modelling of computer experiments with sequential experimental design. Ph.D. thesis, University of Antwerp, Antwerp
Crombecq K, Dhaene T (2010) Generating sequential space-filling designs using genetic algorithms and monte carlo methods. In: Simulated evolution and learning. Lecture notes in computer science, vol 6457. Springer, Berlin, pp 80–84
Crombecq K, De Tommasi L, Gorissen D, Dhaene T (2009) A novel sequential design strategy for global surrogate modeling. In: Winter simulation conference, Austin, Texas, WSC ’09, pp 731–742
Ferguson N, Cummings D, Cauchemez S, Fraser C, Riley S, Meeyai A, Iamsirithaworn S, Burke D (2005) Strategies for containing an emerging influenza pandemic in Southeast Asia. Nature 437(7056):209–214CrossRef
Ferguson N, Cummings D, Fraser C, Cajka J, Cooley P, Burke D (2006) Strategies for mitigating an influenza pandemic. Nature 442(7101):448–452CrossRef
Germann T, Kadau K, Longini Jr I, Macken C (2006) Mitigation strategies for pandemic influenza in the United States. PNAS 103(15):5935–5940CrossRef
Halloran M, Ferguson N, Eubank S, Longini I, Cummings D, Lewis B, Xu S, Fraser C, Vullikanti A, Germann T, et al (2008) Modeling targeted layered containment of an influenza pandemic in the United States. PNAS 105(12):4639–4644CrossRef
Husslage B, Rennen G, Van Dam ER, Den Hertog D (2006) Space-filling Latin hypercube designs for computer experiments. Tilburg UniversityMATH
Kordon AK, Smits GF (2001) Soft sensor development using genetic programming. In: Spector L, Goodman ED, Wu A, Langdon WB, Voigt HM, Gen M, Sen S, Dorigo M, Pezeshk S, Garzon MH, Burke E (eds) Proceedings of the genetic and evolutionary computation conference (GECCO-2001), Morgan Kaufmann, San Francisco, California, pp 1346–1351. http://​www.​cs.​bham.​ac.​uk/​~wbl/​biblio/​gecco2001/​d24.​pdf
Ma J, Ackerman E, Yang J (1993) Parameter sensitivity of a model or viral epidemics simulated with Monte Carlo techniques. I. illness attack rates. Int J Biomed Comput 32:237–253CrossRef
Piedra P, Gaglani M, Kozinetz C, Herschler G, Riggs M, Griffith M, Fewlass C, Watts M, Hessel C, Cordova J, et al (2005) Herd immunity in adults against influenza-related illnesses with use of the trivalent-live attenuated influenza vaccine (CAIV-T) in children. Vaccine 23(13):1540–1548CrossRef
Santner TJ, Williams BJ, Notz WI (2003) The design and analysis of computer experiments. Springer, New YorkCrossRefMATH
Smits G, Kotanchek M (2004) Pareto-front exploitation in symbolic regression, Chap. 17 In: O’Reilly UM, Yu T, Riolo RL, Worzel B (eds) Genetic programming theory and practice II. Springer, Ann Arbor, pp 283–299. doi:10.​1007/​0-387-23254-0_​17
Stijven S, Minnebo W, Vladislavleva K (2011) Separating the wheat from the chaff: on feature selection and feature importance in regression random forests and symbolic regression. In: Proceedings of the 13th annual conference companion on genetic and evolutionary computation, Dublin, GECCO ’11, pp 623–630
Trustable symbolic regression models: using ensembles, interval arithmetic and pareto fronts to develop robust and trust-aware models
Metadata
Title
Prime-Time: Symbolic Regression Takes Its Place in the Real World
Authors
Sean Stijven
Ekaterina Vladislavleva
Arthur Kordon
Lander Willem
Mark E. Kotanchek
Copyright Year
2016
Book
Genetic Programming Theory and Practice XIII

Print ISBN: 978-3-319-34221-4

Electronic ISBN: 978-3-319-34223-8

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-34223-8_14

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