Automatic Design of ANNs by Means of GP for Data Mining Tasks: Iris Flower Classification Problem

1. Haykin, S.: Neural Networks, 2nd edn. Prentice Hall, Englewood Cliffs (1999)

   MATH  Google Scholar 

2. Rabuñal, J.R., Dorado, J. (eds.): Artificial Neural Networks in Real-Life Applications. Idea Group Inc., Hershey (2005)

   Google Scholar 

3. Fisher, R.A.: The use of multiple measurements in taxonomic problems. Annals of Eugenics, 179–188 (1936)

   Google Scholar 

4. Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)

   MATH  Google Scholar 

5. Rivero, D., Rabuñal, J.R., Dorado, J., Pazos, A.: Time Series Forecast with Anticipation using Genetic Programming. In: Cabestany, J., Prieto, A.G., Sandoval, F. (eds.) IWANN 2005. LNCS, vol. 3512, pp. 968–975. Springer, Heidelberg (2005)

   Google Scholar 

6. Bot, M.: Application of Genetic Programming to Induction of Linear Classification Trees. Final Term Project Report, Vrije Universiteit, Amsterdam (1999)

   Google Scholar 

7. Rabuñal, J.R., Dorado, J., Puertas, J., Pazos, A., Santos, A., Rivero, D.: Prediction and Modelling of the Rainfall-Runoff Transformation of a Typical Urban Basin using ANN and GP. Applied Artificial Intelligence (2003)

   Google Scholar 

8. Sutton, R.S.: Two problems with backpropagation and other steepest-descent learning procedure for networks. In: Proc. 8th Annual Conf. Cognitive Science Society, pp. 823–831. Lawrence Erlbaum, Hillsdale (1986)

   Google Scholar 

9. Janson, D.J., Frenzel, J.F.: Training product unit neural networks with genetic algorithms. IEEE Expert 8, 26–33 (1993)

   Article  Google Scholar 

10. Greenwood, G.W.: Training partially recurrent neural networks using evolutionary strategies. IEEE Trans. Speech Audio Processing 5, 192–194 (1997)

    Article  Google Scholar 

11. Alba, E., Aldana, J.F., Troya, J.M.: Fully automatic ANN design: A genetic approach. In: Mira, J., Cabestany, J., Prieto, A.G. (eds.) IWANN 1993. LNCS, vol. 686, pp. 399–404. Springer, Heidelberg (1993)

    Google Scholar 

12. Kitano, H.: Designing neural networks using genetic algorithms with graph generation system. Complex Systems 4, 461–476 (1990)

    MATH  Google Scholar 

13. Yao, X., Liu, Y.: Towards designing artificial neural networks by evolution. Appl. Math. Computation 91(1), 83–90 (1998)

    Article  MATH  MathSciNet  Google Scholar 

14. Harp, S.A., Samad, T., Guha, A.: Toward the genetic synthesis of neural networks. In: Schafer, J.D. (ed.) Proc. 3rd Int. Conf. Genetic Algorithms and Their Applications, pp. 360–369. Morgan Kaufmann, San Mateo (1989)

    Google Scholar 

15. Nolfi, S., Parisi, D.: Evolution of Artificial Neural Networks. In: Handbook of brain theory and neural networks, 2nd edn., pp. 418–421. MIT Press, Cambridge (2002)

    Google Scholar 

16. Turney, P., Whitley, D., Anderson, R.: Special issue on the baldwinian effect. Evolutionary Computation 4(3), 213–329 (1996)

    Article  Google Scholar 

17. Montana, D.J.: Strongly typed genetic programming. Evolutionary Computation 3(2), 199–200 (1995)

    Article  Google Scholar 

18. Mertz, C.J., Murphy, P.M.: UCI repository of machine learning databases (2002), http://www-old.ics.uci.edu/pub/machine-learning-databases

19. Cantú-Paz, E., Kamath, C.: An Empirical Comparison of Combinations of Evolutionary Algorithms and Neural Networks for Classification Problems. IEEE Transactions on systems, Man and Cybernetics – Part B: Cybernetics, 915–927 (2005)

    Google Scholar 

20. Herrera, F., Hervás, C., Otero, J., Sánchez, L.: Un estudio empírico preliminar sobre los tests estadísticos más habituales en el aprendizaje automático. In: Giraldez, R., Riquelme, J.C., Aguilar, J.S. (eds.) Tendencias de la Minería de Datos en España, Red Española de Minería de Datos y Aprendizaje, pp. 403–412 (2004)

    Google Scholar 

21. Gruau, F.: Genetic Micro Programming of Neural Networks. In: Kinnear, K. (ed.) Advances in Genetic Programming, pp. 495–518. MIT Press, Cambridge (1994)

    Google Scholar 

22. Duch, W., Adamczak, R., Grabczewski, K.: A new methodology of extraction, optimisation and application of crisp and fuzzy logical rules. IEEE Transactions on Neural Networks 11(2) (2000)

    Google Scholar 

23. Martinez, A., Goddard, J.: Definición de una red neuronal para clasificación por medio de un programa evolutivo. Mexican Journal of Biomedical Engineering 22, 4–11 (2001)

    Google Scholar 

24. Rabuñal, J.R.: Entrenamiento de redes de neuronas artificiales mediante algoritmos genéticos. Graduate Thesis , University of A Coruña, Spain (1999)

    Google Scholar 

25. Rivero, D., Dorado, J., Rabuñal, J., Pazos, A.: Using Genetic Programmning for Artificial Neural Network Development and Simplification. In: Proceedings of the 5th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics (CIMMACS’06), pp. 65–71. WSEAS Press (2006)

    Google Scholar 

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