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Multi-instance classification through spherical separation and VNS

Tijdschriftbijdrage - Tijdschriftartikel

A two-class classification problem is considered where the objects to be classified are bags of instances in d-space. The classification rule is defined in terms of an open d-ball. A bag is labeled positive if it meets the ball and labeled negative otherwise. Determining the center and radius of the ball is modeled as a SVM-like margin optimization problem. Necessary optimality conditions are derived leading to a polynomial algorithm in fixed dimension. A VNS type heuristic is developed and experimentally tested. The methodology is extended to classification by several balls and to more than two classes.
Tijdschrift: Comput Oper Res
ISSN: 0305-0548
Volume: 52
Pagina's: 326-333
Trefwoorden:Supervised classification, Multi-instance learning, Mixed-integer programming, Variable neighborhoodsearch
  • VABB Id: c:vabb:388822
  • Scopus Id: 84943818968
  • WoS Id: 000343952200019
  • ORCID: /0000-0001-6206-6556/work/84204579
CSS-citation score:1