Nederlands
Contact
Search
OrganisationEEMCS EPrints Service
 |
|
|
||||||||||||||||||||||||||||||||||||
|
|
|
|
|
||||||||||||||||||||||||||||||||||
|
|
|
||||||||||||||||||||||||||||||||||||
|
|
|
|
|
||||||||||||||||||||||||||||||||||
|
|
Sent, D. and van der Gaag, L.C.
(2007)
Enhancing Automated Test Selection in Probabilistic Networks.
In: Proceedings of Artifical Intelligence in Medicine Europe (AIME), 07-11 July 2007, Amsterdam.
pp. 331-335.
Lecture Notes in Artificial Intelligence 4594.
Springer Verlag.
ISSN 0302-9743
Full text available as:
Official URL: http://dx.doi.org/10.1007/978-3-540-73599-1_44  AbstractMost test-selection algorithms currently in use with probabilistic networks select variables myopically, that is, test variables are selected sequentially, on a one-by-one basis, based upon expected information gain. While myopic test selection is not realistic for many medical applications, non-myopic test selection, in which information gain would be computed for all combinations of variables, would be too demanding. We present three new test-selection algorithms for probabilistic networks, which all employ knowledge-based clusterings of variables;
Export this item as: To request a copy of the PDF please email us request copy To correct this item please ask your editor Repository Staff Only: edit this item |
|
|
||||||||||||||||||||||||||||||||||
|
|
|
||||||||||||||||||||||||||||||||||||
|
|
|
|
|
||||||||||||||||||||||||||||||||||
|
|
|
||||||||||||||||||||||||||||||||||||
