Abstract
A concept of learning from observations is presented using a combined theory of subjective and objective probability notions in Bayesian networks with tree structure. The principle of learning is applied to communication nets.
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© 1992 Springer-Verlag Berlin Heidelberg
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Lehmann, F., Seising, R., Walther-Klaus, E. (1992). Machine learning in communication nets. In: Belli, F., Radermacher, F.J. (eds) Industrial and Engineering Applications of Artificial Intelligence and Expert Systems. IEA/AIE 1992. Lecture Notes in Computer Science, vol 604. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0024982
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DOI: https://doi.org/10.1007/BFb0024982
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