Application of hybrid symbolic ensembles to gene expression analyses
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 understa...
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Published in | 2008 9th Symposium on Neural Network Applications in Electrical Engineering pp. 95 - 98 |
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Main Authors | , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.09.2008
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Subjects | |
Online Access | Get full text |
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Summary: | 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). |
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ISBN: | 142442903X 9781424429035 |
DOI: | 10.1109/NEUREL.2008.4685577 |