Abstract
Different experts formulate the rules with different qualities. Additional we may get some information about problem from databases and qualities of information stored in the databases are different. We will propose the quality measure of knowledge we got. We will show how use it for decision process based on Bayes formulae and boosting concept.
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Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification. Wiley Interscience, Hoboken (2000)
Mitchell, T.: Machine Learning. McGraw-Hill, New York (1997)
Puchala, E.: A Bayes Algorithm for the Multitask Pattern Recognition Problem – Direct Approach. In: Sloot, P.M.A., Abramson, D., Bogdanov, A.V., Gorbachev, Y.E., Dongarra, J., Zomaya, A.Y. (eds.) ICCS 2003. LNCS, vol. 2659, Springer, Heidelberg (2003)
Schapire, R.E.: The boosting approach to machine learning: An overview. In: Proc. Of MSRI Workshop on Nonlinear Estimation and Classification, Berkeley, CA (2001)
Walkowiak, K.: A Branch and Bound Algorithm for Primary Routes Assignment in Survivable Connection Oriented Networks. In: Computational Optimization and Applications, February 2004, vol. 27, Kluwer Academic Publishers, Dordrecht (2004)
Wozniak, M.: Concept of the Knowledge Quality Management for Rule-Based Decision System, W. In: Klopotek, M.A., et al. (eds.) Intelligent Information Processing and Web Mining, Springer, Heidelberg (2003)
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Wozniak, M. (2004). Proposition of Boosting Algorithm for Probabilistic Decision Support System. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds) Computational Science - ICCS 2004. ICCS 2004. Lecture Notes in Computer Science, vol 3036. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24685-5_117
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DOI: https://doi.org/10.1007/978-3-540-24685-5_117
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22114-2
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