Cost-conscious comparison of supervised learning algorithms over multiple data sets

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dc.authorid0000-0003-2225-7491
dc.authorid0000-0001-5838-4615
dc.authorid0000-0001-7506-0321
dc.contributor.authorUlaş, Aydınen_US
dc.contributor.authorYıldız, Olcay Taneren_US
dc.contributor.authorAlpaydın, Ahmet İbrahim Ethemen_US
dc.date.accessioned2015-01-15T23:02:04Z
dc.date.available2015-01-15T23:02:04Z
dc.date.issued2012-04
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Computer Engineeringen_US
dc.description.abstractIn the literature, there exist statistical tests to compare supervised learning algorithms on multiple data sets in terms of accuracy but they do not always generate an ordering. We propose Multi(2)Test, a generalization of our previous work, for ordering multiple learning algorithms on multiple data sets from "best" to "worst" where our goodness measure is composed of a prior cost term additional to generalization error. Our simulations show that Multi2Test generates orderings using pairwise tests on error and different types of cost using time and space complexity of the learning algorithms.en_US
dc.description.sponsorshipWe would like to thank Mehmet Gonen for discussions. This work has been supported by the Turkish Academy of Sciences in the framework of the Young Scientist Award Program (EA-TUBA-GEBIP/2001-1-1), Bogazici University Scientific Research Project 07HA101, Turkish Scientific Technical Research Council (TUBITAK) EEEAG 107E127, 107E222 and 109E186en_US
dc.description.sponsorshipWe would like to thank Mehmet Gonen for discussions. This work has been supported by the Turkish Academy of Sciences in the framework of the Young Scientist Award Program (EA-TUBA-GEBIP/2001-1-1), Bogazici University Scientific Research Project 07HA101, Turkish Scientific Technical Research Council (TUBITAK) EEEAG 107E127, 107E222 and 109E186.en_US
dc.description.versionPublisher's Versionen_US
dc.description.versionAuthor Pre-Printen_US
dc.identifier.citationUlaş, A., Yıldz, O. T. & Alpaydın, A. İ. E. (2012). Cost-conscious comparison of supervised learning algorithms over multiple data sets. Pattern Recognition, 45(4), 1772-1781. doi:10.1016/j.patcog.2011.10.005en_US
dc.identifier.doi10.1016/j.patcog.2011.10.005
dc.identifier.endpage1781
dc.identifier.issn0031-3203
dc.identifier.issn1873-5142
dc.identifier.issue4
dc.identifier.scopus2-s2.0-83655191921
dc.identifier.scopusqualityQ1
dc.identifier.startpage1772
dc.identifier.urihttps://hdl.handle.net/11729/449
dc.identifier.urihttp://dx.doi.org/10.1016/j.patcog.2011.10.005
dc.identifier.volume45
dc.identifier.wosWOS:000300459000044
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakScience Citation Index Expanded (SCI-EXPANDED)en_US
dc.institutionauthorYıldız, Olcay Taneren_US
dc.institutionauthorid0000-0001-5838-4615
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherElsevier Sci Ltden_US
dc.relation.ispartofPattern Recognitionen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMachine learningen_US
dc.subjectStatistical testsen_US
dc.subjectClassifier comparisonen_US
dc.subjectModel selectionen_US
dc.subjectModel complexityen_US
dc.subjectStatistical comparisonsen_US
dc.subjectClassificationen_US
dc.subjectTestsen_US
dc.subjectClassifiersen_US
dc.subjectComputer simulationen_US
dc.subjectSupervised learningen_US
dc.subjectGeneralization erroren_US
dc.subjectMachine-learningen_US
dc.subjectMultiple dataen_US
dc.subjectMultiple learning algorithmsen_US
dc.subjectSpace complexityen_US
dc.subjectLearning algorithmsen_US
dc.titleCost-conscious comparison of supervised learning algorithms over multiple data setsen_US
dc.typeArticleen_US
dspace.entity.typePublication

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