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A hybrid discriminative/generative approach to protein fold recognition
support vector machine
statistical classifiers
RDA classifier
protein fold recognition
There are two standard approaches to the classification task: generative, which use training data to estimate a probability model for each class, and discriminative, which try to construct flexible decision boundaries between the classes. An ideal classifier should combine these two approaches. In this paper a classifier combining the well-known support vector machine (SVM) classifier with regularized discriminant analysis (RDA) classifier is presented. The hybrid classifier is used for protein structure prediction which is one of the most important goals pursued by bioinformatics. The obtained results are promising, the hybrid classifier achieves better result than the SVM or RDA classifiers alone. The proposed method achieves higher recognition ratio than other methods described in the literature.
cris.lastimport.scopus | 2024-04-24T02:47:09Z | |
dc.abstract.en | There are two standard approaches to the classification task: generative, which use training data to estimate a probability model for each class, and discriminative, which try to construct flexible decision boundaries between the classes. An ideal classifier should combine these two approaches. In this paper a classifier combining the well-known support vector machine (SVM) classifier with regularized discriminant analysis (RDA) classifier is presented. The hybrid classifier is used for protein structure prediction which is one of the most important goals pursued by bioinformatics. The obtained results are promising, the hybrid classifier achieves better result than the SVM or RDA classifiers alone. The proposed method achieves higher recognition ratio than other methods described in the literature. | pl |
dc.affiliation | Wydział Fizyki, Astronomii i Informatyki Stosowanej : Zakład Technologii Gier | pl |
dc.conference | Hybrid Artificial Intelligence Systems and Applications (HAIS 2010) | pl |
dc.conference.city | San Sebastian | |
dc.conference.country | Hiszpania | |
dc.conference.datefinish | 2010-06-35 | |
dc.conference.datestart | 2010-06-23 | |
dc.conference.indexscopus | true | |
dc.conference.indexwos | true | |
dc.contributor.author | Chmielnicki, Wiesław - 160876 | pl |
dc.contributor.author | Stąpor, Katarzyna | pl |
dc.date.accessioned | 2016-05-10T11:42:47Z | |
dc.date.available | 2016-05-10T11:42:47Z | |
dc.date.issued | 2012 | pl |
dc.description.conftype | international | pl |
dc.description.number | 1 | pl |
dc.description.physical | 194-198 | pl |
dc.description.publication | 0,3 | pl |
dc.description.volume | 75 | pl |
dc.identifier.doi | 10.1016/j.neucom.2011.04.033 | pl |
dc.identifier.eissn | 1872-8286 | pl |
dc.identifier.issn | 0925-2312 | pl |
dc.identifier.uri | http://ruj.uj.edu.pl/xmlui/handle/item/25298 | |
dc.language | eng | pl |
dc.language.container | eng | pl |
dc.rights | Dodaję tylko opis bibliograficzny | * |
dc.rights.licence | bez licencji | |
dc.rights.uri | * | |
dc.subject.en | support vector machine | pl |
dc.subject.en | statistical classifiers | pl |
dc.subject.en | RDA classifier | pl |
dc.subject.en | protein fold recognition | pl |
dc.subtype | ConferenceProceedings | pl |
dc.title | A hybrid discriminative/generative approach to protein fold recognition | pl |
dc.title.journal | Neurocomputing | pl |
dc.title.volume | Brazilian Symposium on Neural Networks (SBRN 2010) ; International Conference on Hybrid Artificial Intelligence Systems (HAIS 2010) | pl |
dc.type | JournalArticle | pl |
dspace.entity.type | Publication |