Advertisement

Graphical Causal Models

  • Luis Enrique SucarEmail author
Chapter
Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

Abstract

This chapter gives an introduction to causal modeling, in particular to causal Bayesian networks. It starts by introducing causal models and their importance. Then causal Bayesian networks are described, including two types of causal reasoning, prediction and counterfactuals. It continues with the topic of learning causal models, presenting one of the state-of-the-art techniques. Finally, it shows an example of learning causal models from real-world data about children with Attention Deficit Hyperactivity Disorder.

Keywords

Attention Deficit Hyperactivity Disorder Bayesian Network Causal Relation Attention Deficit Hyperactivity Disorder Causal Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Aitken, J.S.: Learning Bayesian networks: approaches and issues. Knowl. Eng. Rev. 26(2), 99–157 (2011)CrossRefGoogle Scholar
  2. 2.
    Claassen, T., Heskes, T: A Bayesian approach to constraint based causal inference. In: Proceedings of Uncertainty in Artificial Intelligence (UAI), AUAI Press, pp. 207–216 (2012)Google Scholar
  3. 3.
    Pearl, J.: Causality: Models. Reasoning and Inference. Cambridge University Press, New York (2009)CrossRefGoogle Scholar
  4. 4.
    Sokolova, E., Groot, P., Classen, T., Heskes, T.: Causal discovery from databases with discrete and continuous variables. In: Probabilistic graphical models (PGM). Springer, pp. 442–457 (2014)Google Scholar
  5. 5.
    Spirtes, P., Glymour, C., Scheines, R.: Causation, Prediction, and Search. MIT Press, Cambridge (2000)Google Scholar
  6. 6.
    Wright, S.: Correlation and causation. J. Agric. Res. 20, 557–585 (1921)Google Scholar

Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  1. 1.Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE)Santa María TonantzintlaMexico

Personalised recommendations