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
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"
Conference_Titel :
Neural Network Applications in Electrical Engineering, 2008. NEUREL 2008. 9th Symposium on
Print_ISBN :
978-1-4244-2903-5
DOI :
10.1109/NEUREL.2008.4685577
