Skip to main content
Disciplines
Automotive
Business IT + Informatics
Construction + Real Estate
Electrical Engineering + Electronics
Energy + Sustainability
Insurance + Risk
Finance + Banking
Management + Leadership
Marketing + Sales
Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Start single access now
Request access for companies
EXTENDED SEARCH
Log in
Top

Hint

Swipe to navigate through the chapters of this book

Published in:
Incremental Hough Transform: A New Method for Circle Detection Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Genetic Programming Model Regularization

Authors : César L. Alonso, José Luis Montaña, Cruz Enrique Borges

Published in: Computational Intelligence

Publisher: Springer International Publishing

Log in

Abstract

We propose a tool for controlling the complexity of Genetic Programming models. The tool is supported by the theory of Vapnik-Chervonekis dimension (VCD) and is combined with a novel representation of models named straight line program. Experimental results, implemented on conventional algebraic structures (such as polynomials), show that the empirical risk, penalized by suitable upper bounds for the Vapnik-Chervonenkis dimension, gives a generalization error smaller than the use of statistical conventional techniques such as Bayesian or Akaike information criteria.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter A Targeted Estimation of Distribution Algorithm Compared to Traditional Methods in Feature Selection
next chapter A Radial Basis Function Neural Network-Based Coevolutionary Algorithm for Short-Term to Long-Term Time Series Forecasting
Literature
1.
2.
Alonso, C.L., Montaña, J.L.. Puente, J.: Straight line programs: a new linear genetic programming approach. In:Proceedings of the 20th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), pp. 571–524 (2008)
3.
4.
Berkowitz, S.J.: On computing the determinant in small parallel time using a small number of processors. Inf. Process. Lett. 18, 147–150 (1984) MathSciNetCrossRefMATH
5.
Bernadro, J., Smith, A.: Bayesian Theory. Willey, New York (1994)
6.
Burguisser, P., Clausen, M., Shokrollahi, M.A.: Algebraic Complexity Theory. Springer, New York (1997)
7.
Cherkassky, V., Yunkian, M.: Comparison of model selection fo regression. Neural Comput. 15(7), 1691–1714 (2003) CrossRefMATH
8.
Gabrielov, A.N., Vorobjov, N.: Complexity of Computations with Pfaffian and Noetherian Functions, Normal Forms, Bifurcations and Finiteness Problems in Differential Equations. Kluwer, Dordrecht (2004)
9.
Giusti, M., Heinz, J.: La Détermination des Points Isolés et la Dimension dúne Varieté Agebrique Peut se Faire en Temps Polynomial, Computational Algebraic Geometry and Commutative Algebra, Symposia Matematica XXXIV, Eisenbud, D, Robbiano, L. (eds.), pp. 216–256. Cambridge University Press, Cambridge (1993)
10.
Giusti, M., Heintz, J., Morais, J., Morgentern, J.E., Pardo, L.M.: Straight line programs in geometric elimination theory. J. Pure Appl. algebra 124, 121–146 (1997) MathSciNet
11.
Goldberg, P., Jerrum, M.: Bounding the vapnik-chervonenkis dimension of concept classes parametrizes by real numbers. Mach. Learn. 18, 131–148 (1995) MATH
12.
Gori, M., Maggini, M., Martinelli, E., Soda, G.: Inductive inference from noisy examples using the hybrid finite state filter. IEEE Trans. Neural Networks 9–3, 571–575 (1998) CrossRef
13.
Heintz, J., Roy, M.F., Solerno, P.: Sur la Complexité du Principe de Tarski-Seidenberg. Bulletin de la Societé Mathematique de France 118, 101–126 (1990) MathSciNetMATH
14.
Koza, J.: Genetic Programming: on the Programming of Computers by Means of Natural Selection. The MIT Press, Cambridge (1992)
15.
Nikolaev, N.Y., Iba, H.: Regularization approach to inductive genetic programming. IEEE Trans. Evol. Comput. 5(4), 359–375 (2001) CrossRef
16.
Okley, H.: In: Kinnear, K. (ed.) Advances in Genetic Programming. Two scientific applications of Genetic Programming: Stack filters and nonlinear fitting to chaotic data, pp. 369–389. MIT Press, Cambridge (1994)
17.
Poli, R., Cagnoni, S.: In: Koza, J.R., Deb, K., Dorigo, M., Fogel, D.B., Garzon, M., Iba, H., Riolo, R.L. (eds.) Evolution of Pseudo-coloring Algoritms for Image Enhancement with Interactive Genetic Programming, pp. 269–277. MIT Press, Cambridge (1997)
18.
Shaoning, P., Kasabov, N.: Inductive vs transductive inference. global vs local models: SVM, TSVM and SVMT for gene expression classification problems. In: Proceedings IEEE International Joint Conference on Neural Networks, vol. 2, pp. 1197–1202 (2004)
19.
Tackett, W.A., Carmi, A.: In: Kinnear, K. (ed.) The Donut Problem: Scalability and Generalization in Genetic Programming, Advances in Genetic Programming. MIT Press, Cambridge (1994)
20.
Tenebaum, J.B., Griffiths, T.L., Kemp, C.: Theory Based Bayesian Models of Inductive Learning and Reasoning. Trends in Cognitive Sciences, Kingston, vol. 10(7), pp. 309–318 (2006)
21.
Vapnik, V., Chervonenkis, A.: Ordered risk minimization. Autom. Remote Control 34, 1226–1235 (1974) MathSciNetMATH
22.
Vapnik, V.: Statistical Learning Theory. Willey, New York (1998)
Metadata
Title
Genetic Programming Model Regularization
Authors
César L. Alonso
José Luis Montaña
Cruz Enrique Borges
Copyright Year
2016
Book
Computational Intelligence

Print ISBN: 978-3-319-23391-8

Electronic ISBN: 978-3-319-23392-5

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-23392-5_6

Premium Partner

Neuer Inhalt
    Image Credits