Abstract
Bayesian averaging over Decision Trees (DTs) allows the class posterior probabilities to be estimated, while the DT models are understandable for domain experts. The use of Markov Chain Monte Carlo (MCMC) technique of stochastic approximation makes the Bayesian DT averaging feasible. In this paper we describe a new Bayesian MCMC technique exploiting a sweeping strategy allowing the posterior distribution to be estimated accurately under a lack of prior information. In our experiments with the solar flares data, this technique has revealed a better performance than that obtained with the standard Bayesian DT technique.
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References
Bentley, R.D., et al.: The European Grid of Solar Observations. In: Proc. Solar Cycle and Space Weather Euro Conference, Vico Equense, Italy, p. 603 (2001)
Turmon M., Pap J., Mukhtar S.: Automatically Finding Solar Active Regions Using SOHO/MDI Photograms and Magnetograms. In: Proc. Structure and Dynamics of the Interior of the Sun and Sun-like Stars, Boston (1998)
Zharkova, V.V., Ipson, S.S., Zharkov, S.I., Benkhalil, A., Aboudarham, J., Bentley, R.D.: A Full Disk Image Standardization of the Synoptic Solar Observations at the Meudon Observatory. Solar Physics 214/1, 89 (2003)
Zharkova, V.V., Ipson, S.S., Zharkov, Aboudarham, J., Benkhalil, A.K., Fuller, N.: Solar Feature Catalogues in EGSO. Solar Physics 228/1, 139–150 (2005)
Zharkova, V.V., Ipson, S.S., Qahwaji, R., Zharkov, S., Benkhalil, A.: An Automated Detection of Magnetic Line Inversion and Its Correlation with Filaments Elongation in Solar Images. In: Proc. SMMSP-2003, Barcelona, Spain, pp. 115–121 (2003)
Bader, D.A., Jaja, J., Harwood, D., Davis, L.S.: Parallel Algorithms for Image Enhancement and Segmentation by Region Growing with Experimental Study. In: Proc. IEEE IPPS 1996, p. 414 (1996)
Gao, J., Zhou, M., Wang, H.: A Threshold and Region Growing Method for Filament Disappearance Area Detection in Solar Images. In: Proc. Information Science and Systems, Johns Hopkins University (2001)
Turmon, M., Mukhtar, S., Pap, J.: Bayesian Inference for Identifying Solar Active Regions. In: Proc. Knowledge Discovery and Data Mining (1997)
Kopparapu, S., Desai, U.: Bayesian Approach to Image Interpretation. Kluwer, Dordrecht (2002)
Duda, R.O., Hart, P.E.: Pattern Classification. Wiley Interscience, Chichester (2001)
Breiman, L., Friedman, J., Olshen, R., Stone, C.: Classification and Regression Trees. Belmont, Wadsworth (1984)
Buntine, W.: Learning Classification Trees. Statistics and Computing 2, 63–73 (1992)
Chipman, H., George, E., McCullock, R.: Bayesian CART Model Search. J. American Statistics 93, 935–960 (1998)
Denison, D., Holmes, C., Malick, B., Smith, A.: Bayesian Methods for Nonlinear Classification and Regression. Wiley, Chichester (2002)
Schetinin, V., Partridge, D., Krzanowski, W.J., Everson, R.M., Fieldsend, J.E., Bailey, T.C., Hernandez, A.: Experimental Comparison of Classification Uncertainty for Randomized and Bayesian Decision Tree Ensembles. J. Math. Modeling and Algorithms 4 (2006) (forthcoming)
Schetinin, V., Fieldsend, J.E., Partridge, D., Krzanowski, W.J., Everson, R.M., Bailey, T.C., Hernandez, A.: The Bayesian Decision Tree Technique with a Sweeping Strategy. In: Advances in Intelligent Systems - Theory and Applications. Cooperation with the IEEE Computer Society, Luxembourg (2004)
Quinlan, J.: C4.5: Programs for Machine Learning. Morgan Kaufmann, San Francisco (1993)
Kuncheva, A.: Combining Pattern Classifiers: Methods and Algorithms. Wiley, Chichester (2004)
Blake, C.L., Merz, C.J.: UCI Repository of Machine Learning Datasets. Irvine, University of California (1998), www.ics.uci.edu/mlearn/MLRepository
Fieldsend, J.E., Bailey, T.C., Everson, R.M., Krzanowski, W.J., Partridge, D., Schetinin, V.: Bayesian Inductively Learned Modules for Safety Critical Systems. In: Proceedings of the 35th Symposium on the Interface, Computing Science and Statistics, US, Salt Lake City (2003)
Green, P.: Reversible Jump Markov Chain Monte Carlo Computation and Bayesian Model Determination. Biometrika 82, 711–732 (1995)
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Schetinin, V., Zharkova, V., Zharkov, S. (2006). Bayesian Decision Tree Averaging for the Probabilistic Interpretation of Solar Flare Occurrences. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893011_67
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DOI: https://doi.org/10.1007/11893011_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46542-3
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