Pedrycz, Witold - ed. ; Korbicz, Józef (1951- ) - ed.
Possibilistic networks constitute a promising framework for efficient treatment of uncertain and imprecise information in knowledge-based systems. In this paper, we propose a new method for induction of the structure (the qualitative part) and the attached possibility distributions (the quantitative part) of a possibilistic network from a database of sample cases that may contain imprecise or missing values. ; It turns out that a modified random-set approach to the semantics of possibility distributions is adequate to provide a possibilistic interpretation of the databases under consideration. Since constructing a possibilistic network can be viewed as a generalization of the structure identification problem in relational data, we have to overcome well-known complexity problems. ; Therefore we present an efficient Greedy search structure induction algorithm for possibilistic networks that has successfully been applied to construct a non-trivial network of practical interest from a given database.
Zielona Góra: Uniwersytet Zielonogórski
AMCS, volume 6, number 3 (1996) ; click here to follow the link
Biblioteka Uniwersytetu Zielonogórskiego
Nov 5, 2024
Nov 17, 2020
60
https://zbc.uz.zgora.pl/publication/64463
Edition name | Date |
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Automated construction of possibilistic networks from data | Nov 5, 2024 |
Beliczyński, Bartłomiej - red.
Krasoń, Ewa Kaczorek, Tadeusz - ed.
Trzaska, Zdzisław W. Kaczorek, Tadeusz - ed.
Xu, Li Saito, Osami Abe, Kenichi Kaczorek, Tadeusz - ed.
Young, K. David Yu, Xinghuo - red.
Xu, Jian-Xin Song, Yanbin Yu, Xinghuo - red.
Stotsky, Alexander A. Hedrick, J. Karl Yip, P.P. Yu, Xinghuo - red.
Hara, Masaaki Furuta, Katsuhisa Pan, Yaodong Hoshino, Tasuku Yu, Xinghuo - red.