A linear programming approach to multiple instance learning

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dc.contributor.authorKüçükaşçı, Emel Şeyma
dc.contributor.authorBaydoğan, Mustafa Gökçe
dc.contributor.authorTaşkın, Z. Caner
dc.date.accessioned2022-01-17T08:40:53Z
dc.date.available2022-01-17T08:40:53Z
dc.date.issued2021en_US
dc.departmentFakülteler, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.description.abstractMultiple instance learning (MIL) aims to classify objects with complex structures and covers a wide range of real-world data mining applications. In MIL, objects are represented by a bag of instances instead of a single instance, and class labels are provided only for the bags. Some of the earlier MIL methods focus on solving MIL problem under the standard MIL assumption, which requires at least one positive instance in positive bags and all remaining instances are negative. This study proposes a linear programming framework to learn instance level contributions to bag label without emposing the standart assumption. Each instance of a bag is mapped to a pseudo-class membership estimate and these estimates are aggregated to obtain the bag-level class membership in an optimization framework. A simple linear mapping enables handling various MIL assumptions with adjusting instance contributions. Our experiments with instance-dissimilarity based data representations verify the effectiveness of the proposed MIL framework. Proposed mathematical models can be solved efficiently in polynomial time.en_US
dc.identifier.doi10.3906/elk-2009-144en_US
dc.identifier.endpage2201en_US
dc.identifier.scopus2-s2.0-85112724665en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage2186en_US
dc.identifier.trdizinid524101en_US
dc.identifier.urihttps://hdl.handle.net/11467/5161
dc.identifier.urihttps://doi.org/10.3906/elk-2009-144
dc.identifier.volume29en_US
dc.identifier.wosWOS:000681248900004en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.publisherTübitaken_US
dc.relation.ispartofTurkish Journal of Electrical Engineering & Computer Sciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMultiple instance learningen_US
dc.subjectClassificationen_US
dc.subjectLinear programmingen_US
dc.subjectOptimizationen_US
dc.titleA linear programming approach to multiple instance learningen_US
dc.typeArticleen_US

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