PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification

  • Babak HodjatEmail author
  • Hormoz Shahrzad
  • Risto Miikkulainen
  • Lawrence Murray
  • Chris Holmes
Part of the Genetic and Evolutionary Computation book series (GEVO)


The EC-Star rule-set representation is extended to allow probabilistic classifiers. This allows the distributed age-layered evolution of probabilistic rule sets. The method is tested on 20 UCI data problems, as well as a larger dataset of arterial blood pressure waveforms. Results show consistent improvement in all cases compared to binary classification rule-sets.


Genetic programming Evolutionary computation Probabilistic rule-sets Distributed processing Time-series classification Medical diagnosis 


  1. 1.
    Asuncion, A., Newman, D.: UCI machine learning repository (2007)Google Scholar
  2. 2.
    De Raedt, L., Thon, I.: Probabilistic rule learning. In: Inductive Logic Programming, pp. 47–58. Springer, Berlin (2010)Google Scholar
  3. 3.
    Deng, H., Runger, G., Tuv, E., Vladimir, M.: A time series forest for classification and feature extraction. Inf. Sci. 239, 142–153 (2013)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Goldberger, A.L., Amaral, L.A., Glass, L., Hausdorff, J.M., Ivanov, P.C., Mark, R.G., Mietus, J.E., Moody, G.B., Peng, C.K., Stanley, H.E.: Physiobank, physiotoolkit, and physionet components of a new research resource for complex physiologic signals. Circulation 101(23), e215–e220 (2000)CrossRefGoogle Scholar
  5. 5.
    Hodjat, B., Shahrzad, H.: Introducing an age-varying fitness estimation function. In: Genetic Programming Theory and Practice X, pp. 59–71. Springer, Berlin (2013)Google Scholar
  6. 6.
    Hodjat, B., Hemberg, E., Shahrzad, H., OReilly, U.M.: Maintenance of a long running distributed genetic programming system for solving problems requiring big data. In: Genetic Programming Theory and Practice XI, pp. 65–83. Springer, Berlin (2014)Google Scholar
  7. 7.
    Klir, G., Yuan, B.: Fuzzy Sets and Fuzzy Logic, vol. 4. Prentice Hall, Upper Saddle River, NJ (1995)Google Scholar
  8. 8.
    OReilly, U.M., Wagy, M., Hodjat, B.: Ec-star: a massive-scale, hub and spoke, distributed genetic programming system. In: Genetic Programming Theory and Practice X, pp. 73–85. Springer, Berlin (2013)Google Scholar
  9. 9.
    Polson, N.G., Scott, J.G., Windle, J.: Bayesian inference for logistic models using pólya–gamma latent variables. J. Am. Stat. Assoc. 108(504), 1339–1349 (2013)CrossRefGoogle Scholar
  10. 10.
    Smith, S.F.: A learning system based on genetic adaptive algorithms (1980)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Babak Hodjat
    • 1
    Email author
  • Hormoz Shahrzad
    • 1
  • Risto Miikkulainen
    • 1
  • Lawrence Murray
    • 2
  • Chris Holmes
    • 2
  1. 1.Sentient TechnologiesSan FranciscoUSA
  2. 2.University of OxfordOxfordUK

Personalised recommendations