Polyhedral separation via difference of convex (DC) programming
Francesco, Massimo Di
;Gaudioso, Manlio;Gorgone, Enrico;Manca, Benedetto
2021-01-01
Abstract
We consider polyhedral separation of sets as a possible tool in supervised classification. In particular, we focus on the optimization model introduced by Astorino and Gaudioso (J Optim Theory Appl 112(2):265–293, 2002) and adopt its reformulation in difference of convex (DC) form. We tackle the problem by adapting the algorithm for DC programming known as DCA. We present the results of the implementation of DCA on a number of benchmark classification datasets.File | Dimensione | Formato | |
---|---|---|---|
Astorino2021_Article_PolyhedralSeparationViaDiffere.pdf accesso aperto
Tipologia: versione post-print
Dimensione 275.26 kB
Formato Adobe PDF
|
275.26 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.