Corpus ID: 13573655

Discover Probabilistic Knowledge from Databases Using Evolutionary Computation and Minimum Description Length Principle

@inproceedings{Lam2006DiscoverPK,
  title={Discover Probabilistic Knowledge from Databases Using Evolutionary Computation and Minimum Description Length Principle},
  author={Wai Lam and M. Wong and K. Leung and Po Shun Ngan},
  year={2006}
}
We have developed a new approach (MDLEP) to learning Bayesian network structures based on the Minimum Description Length (MDL) principle and Evolutionary Programming (EP). It integrates a MDL metric founded on information theory and several new genetic operators including structure-guided operators, a knowledge-guided operator, a freeze operator, and a defrost operator for the discovery process. In contrast, existing techniques based on genetic algorithms (GA) only adopt classical genetic… Expand
3 Citations

Figures and Tables from this paper

Evolving dynamic Bayesian networks with Multi-objective genetic algorithms
  • 29
  • PDF
Automated Discovery of Numerical Approximation Formulae via Genetic Programming
  • 29
  • PDF

References

SHOWING 1-10 OF 20 REFERENCES
Structure Learning of Bayesian Networks by Genetic Algorithms: A Performance Analysis of Control Parameters
  • 375
  • Highly Influential
  • PDF
LEARNING BAYESIAN BELIEF NETWORKS: AN APPROACH BASED ON THE MDL PRINCIPLE
  • 839
  • PDF
Bayesian Network Refinement Via Machine Learning Approach
  • Wai Lam
  • Computer Science
  • IEEE Trans. Pattern Anal. Mach. Intell.
  • 1998
  • 56
Learning Bayesian network structures by searching for the best ordering with genetic algorithms
  • 263
Bayesian Networks
  • J. Pearl
  • Computer Science
  • Encyclopedia of Social Network Analysis and Mining. 2nd Ed.
  • 1998
  • 1,050
  • PDF
Evolutionary Program Induction Directed by Logic Grammars
  • M. Wong
  • Computer Science, Medicine
  • Evolutionary Computation
  • 1997
  • 57
  • PDF
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
  • 3,475
  • PDF
The Computational Complexity of Probabilistic Inference Using Bayesian Belief Networks
  • G. Cooper
  • Mathematics, Computer Science
  • Artif. Intell.
  • 1990
  • 1,968
  • PDF
A Bayesian Method for the Induction of Probabilistic Networks from Data
  • 1,597
  • Highly Influential
  • PDF
Theory Refinement on Bayesian Networks
  • 730
  • PDF
...
1
2
...