Variable Ordering in the Conditional Independence Bayesian Classifier Induction Process: An Evolutionary Approach

@article{Hruschka2007VariableOI,
  title={Variable Ordering in the Conditional Independence Bayesian Classifier Induction Process: An Evolutionary Approach},
  author={Estevam R. Hruschka and Edimilson Batista dos Santos and Sebastian D. C. de O. Galv{\~a}o},
  journal={7th International Conference on Hybrid Intelligent Systems (HIS 2007)},
  year={2007},
  pages={204-209}
}
This work proposes, implements and discusses a hybrid Bayes/genetic collaboration (VOGAC-MarkovPC) designed to induce conditional independence Bayesian classifiers from data. The main contribution is the use of MarkovPC algorithm in order to reduce the computational complexity of a genetic algorithm (GA) designed to explore the variable orderings (VOs) in order to optimize the induced classifiers. Experiments performed in a number of datasets revealed that VOGAC-MarkovPC required less than 25… CONTINUE READING