DocumentCode :
2222503
Title :
Practical aspects of efficient forward selection in decomposable graphical models
Author :
Altmueller, Stephan M. ; Haralick, Robert M.
Author_Institution :
Dept. of Comput. Sci., City Univ. of New York, NY, USA
fYear :
2004
fDate :
15-17 Nov. 2004
Firstpage :
710
Lastpage :
715
Abstract :
We discuss efficient forward selection in the class of decomposable graphical models. This subclass of graphical models has a number of desirable properties. The contributions of This work are twofold. First we improve an existing algorithm by addressing cases previously not considered. Second we extend the algorithm to reflect model graphs with multiple disconnected components. We further present experimental results that apply this approach to a real dataset and discuss its properties. We belief that the presented approach is applicable to a wide area of fields and problems.
Keywords :
computational complexity; graph theory; learning (artificial intelligence); statistical distributions; decomposable graphical model; efficient forward selection; polynomial time algorithm; Computer science; Data mining; Graphical models; Inference algorithms; Information retrieval; Large-scale systems; Pattern recognition; Polynomials; Probability distribution; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence, 2004. ICTAI 2004. 16th IEEE International Conference on
ISSN :
1082-3409
Print_ISBN :
0-7695-2236-X
Type :
conf
DOI :
10.1109/ICTAI.2004.100
Filename :
1374258
Link To Document :
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