Feature selection for splice site prediction: A new method using EDA-based feature ranking |
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| Authors: | Yvan?Saeys,Sven?Degroeve,Dirk?Aeyels,Pierre?Rouzé,Yves?Van de Peer mailto:yves.vandepeer@psb.ugent.be" title=" yves.vandepeer@psb.ugent.be" itemprop=" email" data-track=" click" data-track-action=" Email author" data-track-label=" " >Email author |
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| Affiliation: | 1.Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB),Ghent University,Ghent,Belgium;2.SYSTeMS Research Group,Ghent University,Belgium;3.Laboratoire associé de l'INRA (France),Ghent University,Ghent,Belgium |
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| Abstract: | ![]()
Background The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data. |
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