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http://dx.doi.org/10.5391/JKIIS.2007.17.5.684

Determining Direction of Conditional Probabilistic Dependencies between Clusters  

Jung, Sung-Won (한국과학기술원 바이오 및 뇌 공학과)
Lee, Do-Heon (한국과학기술원 바이오 및 뇌 공학과)
Lee, Kwang-H. (한국과학기술원 바이오 및 뇌 공학과, AITrc)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.17, no.5, 2007 , pp. 684-690 More about this Journal
Abstract
We describe our method to predict the direction of conditional probabilistic dependencies between clusters of random variables. Selected variables called 'gateway variables' are used to predict the conditional probabilistic dependency relations between clusters. The direction of conditional probabilistic dependencies between clusters are predicted by finding directed acyclic graph (DAG)-shaped dependency structure between the gateway variables. We show that our method shows meaningful prediction results in determining directions of conditional probabilistic dependencies between clusters.
Keywords
order prediction; Bayesian network; conditional probabilistic dependency;
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1 H. Zhou and S. Sakane, 'Mobile Robot Localization Using Active Sensing Based on Bayesian Network Inference,' Robotics and Autonomous Systems, Vol. 55, pp. 292-305, 2007   DOI   ScienceOn
2 B. Abramson, J. Brown, W. Edwards, A. Murphy and R. L. Winkler, 'Hailfinder: A Bayesian system for Forecasting Severe Weather,' International Journal of Forecasting, Vol. 12, pp. 57-71, 1996   DOI   ScienceOn
3 S. Acid and L. M. Campos, 'BENEDICT: An Algorithm for Learning Probabilistic Belief Networks,' In Proceedings of 6th International Conference IPMU'96, Grenade, pp. 979-984, 1996
4 Suzuki, 'Learning Bayesian Belief Networks Based on the MDL Principle: An Efficient Algorithm using the Branch and Bound Technique,' IEICE Trans. Information and Systems, Vol. E81-D, pp. 356-367, 1999
5 G. F. Cooper and E. Herskovitz, 'A Bayesian Method for the Induction of Probabilistic Networks from Data,' Machine Learning, Vol. 9, pp, 309-347, 1992
6 L. Uusitalo, 'Advantages and Challenges of Bayesian Networks in Environmental modelling,' Ecological Modelling, Vol. 203, pp. 312-318, 2007   DOI   ScienceOn
7 I. A. Beinlich, H. J. Suermondt, R. M. Chavez and G. F. Cooper, 'The ALARM Monitoring System: A Case Study with Two Probabilistic Inference Techniques for Belief Networks,' Proceedings of the Second European Conference on Artificial Intelligence in Medicine, 1989
8 D. Heckerman, D. Gerger and D. M. Chickering, 'Learning Bayesian Networks: The Combination of Knowledge and Statistical Data,' Machine Learning, Vol. 20, pp. 197-243, 1995
9 B. R. Cobb and P. P. Shenoy, 'Inference in Hybrid Bayesian Networks with Mixtures of Truncated Exponentials,' International Journal of Approximate Reasoning, Vol. 41, pp. 257-286, 2006   DOI   ScienceOn
10 N. Friedman, I. Nachman and D. Pe'er, 'Learning Bayesian Network Structure from Massive Datasets: The 'Sparse Candidate' Algorithm,' Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, pp. 206-215, 1999
11 S. Andreassen, R. Hovorka, J. Benn, K. G. Olesen and E. R. Carson, 'A Model-Based Approach to Insulin Adjustment,' Proceedings of the Third Conference on Artificial Intelligence in Medicine, pp. 239-248, 1991
12 E. Herskovitz, G. Cooper, 'Kutato: An Entropy-Driven System for Construction of Probabilistic Expert Systems from Databases,' In Proceedings of 6th International Conference on Uncertainty in Artificial Intelligence, Cambridge, MA, pp. 54-62, 1990
13 D. E. Heckerman, E. J. Horvitz and B. N. Nathwani, 'Toward Normative Expert Systems: Part I The Pathfinder Project,' Methods of Information in Medicine, Vol. 31, pp. 90-105, 1992   DOI
14 B. R. Cobb and P. P. Shenoy, 'Operations for Inference in Continuous Bayesian Networks with Linear Deterministic Variables,' International Journal of Approximate Reasoning, Vol. 42, pp. 21-36, 2006   DOI   ScienceOn
15 L. E. Brown, I. Tsamardinos and C. F. Aliferis, 'A Novel Algorithm for Scalable and Accurate Bayesian Network Learning,' MEDINFO, 2004
16 L. Sun and P. P. Shenoy, 'Using Bayesian Networks for Bankruptcy Prediction: Some Methodological Issues,' European Journal of Operational Research, Vol. 180, pp. 738-753, 2007   DOI   ScienceOn
17 H. J. Suermondt and G. F. Cooper, 'A Combination of Exact Algorithms for Inference on Bayesian Belief Networks,' International Journal of Approximate Reasoning, Vol. 5, pp. 521-542, 1991   DOI   ScienceOn