Referenced Items are not available for this document.
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).
Published in:
Neural Network Applications in Electrical Engineering, 2008. NEUREL 2008. 9th Symposium on
Date of Conference: 25-27 Sept. 2008
- Page(s):
- 95 - 98
- E-ISBN :
- 978-1-4244-2904-2
- Print ISBN:
- 978-1-4244-2903-5
- INSPEC Accession Number:
- 10397983
- Conference Location :
- Belgrade
- Digital Object Identifier :
- 10.1109/NEUREL.2008.4685577
- Product Type:
- Conference Publications
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