Maximizing benefit of classifications using feature intervals

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dc.citation.epage345en_US
dc.citation.spage339en_US
dc.citation.volumeNumber2773en_US
dc.contributor.authorİkizler, Nazlıen_US
dc.contributor.authorGüvenir, H. Altayen_US
dc.coverage.spatialOxford, UKen_US
dc.date.accessioned2016-02-08T11:55:23Z
dc.date.available2016-02-08T11:55:23Zen_US
dc.date.issued2003en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionDate of Conference: KES: International Conference on Knowledge-Based and Intelligent Information and Engineering Systems 7th INternational Conferenceen_US
dc.descriptionDate of Conference: September 2003en_US
dc.description.abstractThere is a great need for classification methods that can properly handle asymmetric cost and benefit constraints of classifications. In this study, we aim to emphasize the importance of classification benefits by means of a new classification algorithm, Benefit-Maximizing classifier with Feature Intervals (BMFI) that uses feature projection based knowledge representation. Empirical results show that BMFI has promising performance compared to recent cost-sensitive algorithms in terms of the benefit gained.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T11:55:23Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2003en_US
dc.identifier.doi10.1007/978-3-540-45224-9_48en_US
dc.identifier.doi10.1007/978-3-540-45224-9en_US
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/11693/27510en_US
dc.language.isoEnglishen_US
dc.publisherSpringer, Berlin, Heidelbergen_US
dc.relation.isversionofhttps://doi.org/10.1007/978-3-540-45224-9_48en_US
dc.relation.isversionofhttps://doi.org/10.1007/978-3-540-45224-9en_US
dc.source.titleKnowledge-Based Intelligent Information and Engineering Systemsen_US
dc.subjectAlgorithmsen_US
dc.subjectClassification (of information)en_US
dc.subjectConstraint Theoryen_US
dc.subjectData Miningen_US
dc.subjectError Analysisen_US
dc.subjectKnowledge Representationen_US
dc.subjectMatrix Algebraen_US
dc.subjectSet Theoryen_US
dc.subjectKnowledge Based Systemsen_US
dc.subjectKnowledge Representationen_US
dc.subjectBenefit-Maximizing Classifier with Feature Intervals (BMFI)en_US
dc.subjectCost-Sensitive Classificationen_US
dc.subjectCost-Sensitive Learningen_US
dc.subjectFeature Intervalsen_US
dc.subjectLearning Systemsen_US
dc.subjectClassification (of information)en_US
dc.subjectAsymmetric Costsen_US
dc.subjectClassification Algorithmen_US
dc.subjectClassification Methodsen_US
dc.subjectCost-Sensitive Algorithmen_US
dc.subjectFeature Projectionen_US
dc.titleMaximizing benefit of classifications using feature intervalsen_US
dc.typeConference Paperen_US

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