Learning Bayesian Networks Using Evolutionary Algorithm and a Variant of MDL Score

1. Heckerman, D.: Bayesian networks for data mining. Data Mining and Knowledge Discovery 1(1), 79–119 (1997)

   Article  Google Scholar 

2. Lam, W., Bacchus, F.: Learning Bayesian belief networks: An approach based on the MDL principle. Computational Intelligence 10, 269–293 (1994)

   Article  Google Scholar 

3. Zhang, S., Wang, X.: Algorithm for Bayesian networks structure learning based on information entropy. Mini-Micro Computer Systems 26(6), 983–986 (2005)

   Google Scholar 

4. Chickering, D.: Learning equivalence classes of Bayesian-network structures. Journal of Machine Learning Research 2, 445–498 (2002)

   Article  MATH  Google Scholar 

5. Tsamardinos, I., Aliferis, C., Statnikov, A.: Time and sample efficient discovery of Markov blankets and direct causal relations. In: 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 673–678. ACM Press, USA (2003)

   Chapter  Google Scholar 

6. Spirtes, P., Glymour, C., Scheines, R.: Causation, prediction and search, 2nd edn. MIT Press, Cambridge, MA (2001)

   MATH  Google Scholar 

7. Cheng, J., Greiner, R., Kelly, J., Bell, D.A., Liu, W.: Learning Bayesian networks from data: an information-theory based approach. The Artificial Intelligence Journal 137, 43–90 (2002)

   Article  MATH  Google Scholar 

8. Ioannis, T., Laura, E., Constantin, F.A.: The max-min hill-climbing Bayesian networks from data. Machine Learning 65(1), 31–78 (2006)

   Article  Google Scholar 

9. Larranaga, P.M.P., et al.: Structure learning of Bayesian networks by genetic algorithms: A performance analysis of control parameters. IEEE Journal on Pattern Analysis and Machine Intelligence 18(9), 912–926 (1996)

   Article  Google Scholar 

10. Myers, J., Laskey, K., Levitt, T.: Learning Bayesian networks from incomplete data with stochastic search algorithms. In: 15th Conf. on Uncertainty in Artificial Intelligence (1999)

    Google Scholar 

11. Friedman, N.: The Bayesian structural EM algorithm. In: Fourteenth Conf. on Uncertainty in Artificial Intelligence (1998)

    Google Scholar 

12. Tian, F., Lu, Y., Shi, C.: Learning Bayesian networks with hidden variables using the combination of EM and evolutionary algorithm. In: Cheung, D., Williams, G.J., Li, Q. (eds.) PAKDD 2001. LNCS (LNAI), vol. 2035, pp. 568–574. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

13. Tian, F., Zhang, H., Lu, Y.: Learning Bayesian networks from incomplete data based on EMI method. In: Proceedings of ICDM 2003 Melbourne, Florida, USA, pp. 323–330 (2003)

    Google Scholar 

14. Settimi, R., Smith, J.Q.: On the geometry of Bayesian graphical models with hidden variables. In: Proceedings of UAI 1998, Morgan Kaufmann, Madison, WI (1998)

    Google Scholar 

15. Martin, J., VanLehn, K.: Discrete factor analysis: Learning hidden variables in Bayesian networks. Technical report, Department of Computer Science, University of Pittsburgh, PA (1995)

    Google Scholar 

Download references