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  New challenges for feature selection in the life sciences

Borgwardt, K. (2009). New challenges for feature selection in the life sciences. In 23rd European Conference on Operational Research (Euro XXIII) (pp. 217).

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-28D9-C Version Permalink: http://hdl.handle.net/21.11116/0000-0003-28DA-B
Genre: Meeting Abstract

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Borgwardt, KM1, 2, Author              
Affiliations:
1Former Research Group Machine Learning and Computational Biology, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_2528696              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: The life sciences create new challenges for feature selection in data mining: First, there is a need for feature selection on structured data such as strings and graphs. Second, a deeper theoretical understanding of the connections between existing feature selection approaches would be beneficial, to explain the discrepancies in their results on the same datasets. Third, the large number of features poses a computational and algorithmic challenge and requires the development of new, efficient selection techniques. In this talk, we will present our work on these three topics.

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 Dates: 2009-07
 Publication Status: Published online
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Title: 23rd European Conference on Operational Research (Euro XXIII)
Place of Event: Bonn, Germany
Start-/End Date: 2009-07-05 - 2009-07-08

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Title: 23rd European Conference on Operational Research (Euro XXIII)
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: TE-30-2 Start / End Page: 217 Identifier: -