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Research Centre
Data - Algorithms - Decision Making
Data - Algorithms - Decision Making
Established in 2005 under support of MŠMT ČR (project 1M0572)
Publications
Conditional Independence and Compositional Models for Belief Functions
Typ:
Conference paper
Authors:
Proceedings name:
The 11th Czech-Japan Seminář on Data Analysis and Decision Making under Uncertainty
Publisher:
The Kao Foundations for Arts and Sciences
Serie:
Sendai
Year:
2008
Keywords:
conditional independence, belief function, multidimensional
Anotation:
The contribution discusses an approach utilizing properties of conditional independence relations that enables assembling a multidimensional model from a system of its simple submodels. Unfortunately, the concept of conditional independence has been for belief functions defined in several ways and none of them fully meets the necessary requirements. Therefore a new approach how to define conditional independence for belief functions is introduced.