Pedrycz, Witold - ed. ; Korbicz, Józef - 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) ; kliknij tutaj, żeby przejść
Biblioteka Uniwersytetu Zielonogórskiego
2021-09-02
2020-11-17
55
https://zbc.uz.zgora.pl/publication/64463
Nazwa wydania | Data |
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Automated construction of possibilistic networks from data | 2021-09-02 |
Korbicz, Józef - red.
Korbicz, Józef - red. Uciński, Dariusz - red.
Korbicz, Józef - red. Uciński, Dariusz - red.
Korbicz, Józef - red. Uciński, Dariusz - red.
Korbicz, Józef - red. Uciński, Dariusz - red.
Korbicz, Józef - red. Uciński, Dariusz - red.
Korbicz, Józef - red. Uciński, Dariusz - red.
Beliczyński, Bartłomiej - red.