On the VC-dimension of univariate decision trees
dc.authorid | 0000-0001-5838-4615 | |
dc.contributor.author | Yıldız, Olcay Taner | en_US |
dc.date.accessioned | 2019-08-31T12:10:23Z | |
dc.date.accessioned | 2019-08-05T16:04:58Z | |
dc.date.available | 2019-08-31T12:10:23Z | |
dc.date.available | 2019-08-05T16:04:58Z | |
dc.date.issued | 2012 | |
dc.department | Işık Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | en_US |
dc.department | Işık University, Faculty of Engineering, Department of Computer Engineering | en_US |
dc.description.abstract | In this paper, we give and prove lower bounds of the VC-dimension of the univariate decision tree hypothesis class. The VC-dimension of the univariate decision tree depends on the VC-dimension values of its subtrees and the number of inputs. In our previous work (Aslan et al., 2009), we proposed a search algorithm that calculates the VC-dimension of univariate decision trees exhaustively. Using the experimental results of that work, we show that our VC-dimension bounds are tight. To verify that the VC-dimension bounds are useful, we also use them to get VC-generalization bounds for complexity control using SRM in decision trees, i.e., pruning. Our simulation results shows that SRM-pruning using the VC-dimension bounds finds trees that are more accurate as those pruned using cross-validation. | en_US |
dc.description.version | Publisher's Version | en_US |
dc.identifier.citation | Yıldız, O. T. (2012). On the VC-dimension of univariate decision trees. Paper present et the ICPRAM 2012 - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods, 205-210. doi:10.5220/0003777202050210 | en_US |
dc.identifier.endpage | 210 | |
dc.identifier.isbn | 9789898425980 | |
dc.identifier.scopus | 2-s2.0-84862192969 | |
dc.identifier.scopusquality | N/A | |
dc.identifier.startpage | 205 | |
dc.identifier.uri | https://hdl.handle.net/11729/1934 | |
dc.identifier.uri | http://dx.doi.org/10.5220/0003777202050210 | |
dc.identifier.volume | 1 | |
dc.indekslendigikaynak | Scopus | en_US |
dc.institutionauthor | Yıldız, Olcay Taner | en_US |
dc.institutionauthorid | 0000-0001-5838-4615 | |
dc.language.iso | en | en_US |
dc.peerreviewed | Yes | en_US |
dc.publicationstatus | Published | en_US |
dc.relation.ispartof | ICPRAM 2012 - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Decision trees | en_US |
dc.subject | VC-dimension | en_US |
dc.subject | Pattern recognition | en_US |
dc.subject | Cross validation | en_US |
dc.subject | Lower bounds | en_US |
dc.subject | Search algorithms | |
dc.subject | Subtrees | en_US |
dc.subject | Univariate | en_US |
dc.title | On the VC-dimension of univariate decision trees | en_US |
dc.type | Conference Object | en_US |
dspace.entity.type | Publication |
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