Algorithms for discovery of multiple Markov boundaries

@article{Statnikov2013AlgorithmsFD,
  title={Algorithms for discovery of multiple Markov boundaries},
  author={Alexander R. Statnikov and Jan Lemeire and Constantin F. Aliferis},
  journal={Journal of machine learning research : JMLR},
  year={2013},
  volume={14},
  pages={
          499-566
        }
}
Algorithms for Markov boundary discovery from data constitute an important recent development in machine learning, primarily because they offer a principled solution to the variable/feature selection problem and give insight on local causal structure. Over the last decade many sound algorithms have been proposed to identify a single Markov boundary of the response variable. Even though faithful distributions and, more broadly, distributions that satisfy the intersection property always have a… CONTINUE READING

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Learning Causal Models of Multivariate Systems and the Value of It for the Performance Modeling of Computer Programs

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