DocumentCode
3629708
Title
Application of hybrid symbolic ensembles to gene expression analyses
Author
Vladislav Miskovic;Milan Milosavljevic
Author_Institution
Faculty of Informatics and Management, Singidunum University, 11000 Belgrade, Serbia
fYear
2008
Firstpage
95
Lastpage
98
Abstract
This paper considers a class of hybrid (heterogeneous) ensembles purely composed of symbolic elements. In learning diagnostic rules from gene expressions they demonstrate a significant improvement of accuracy with a small number of ensemble elements. This makes them suitable for learning of understandable knowledge, leading to diagnosis and its explanation in original terms (attributes).
Keywords
"Gene expression","Diversity reception","Diversity methods","Hybrid power systems","Stacking","Radio frequency","Accuracy","Voting","Neural networks","Learning systems"
Publisher
ieee
Conference_Titel
Neural Network Applications in Electrical Engineering, 2008. NEUREL 2008. 9th Symposium on
Print_ISBN
978-1-4244-2903-5
Type
conf
DOI
10.1109/NEUREL.2008.4685577
Filename
4685577
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