Title
Ensembles of hybrid intelligent experts: Extending the power of optimal linear combiners
Abstract
In the present paper we generalize the idea of Optimal Linear Combiners that are used to aggregate information from different sources providing estimates about a specific quantity. Two linear models are introduced, along with their analysis, which combine related components of information when more than one variable is to be predicted. The models' purpose is to produce point estimates of better accuracy in terms of mean squared error. Experimental results dealing with a functional approximation problem demonstrate that the generalized Optimal Linear Combiners suggested yield higher accuracy when compared to other combiners such as the Simple Average, or the conventional Optimal Linear Combiners.
Publication Date
12-1-1997
Publication Title
Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume
2
Number of Pages
1350-1355
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
0031335325 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0031335325
STARS Citation
Anagnostopoulos, Georgios C.; Georgiopoulos, Michael; and Nickerson, David, "Ensembles of hybrid intelligent experts: Extending the power of optimal linear combiners" (1997). Scopus Export 1990s. 3123.
https://stars.library.ucf.edu/scopus1990/3123