Optimal Subset Selection for Classification through SAT Encodings (Contributo in atti di convegno)

Type

• Contributo in atti di convegno (Classe)
• Prodotto della ricerca (Classe)

Label

• Optimal Subset Selection for Classification through SAT Encodings (Contributo in atti di convegno) (literal)

Anno

• 2008-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

• 10.1007/978-0-387-09695-7_30 (literal)

Alternative label

• Angiulli Fabrizio; Basta Stefano (2008)
  Optimal Subset Selection for Classification through SAT Encodings
  in IFIP International Conference on Arti¯cial Intelligence in Theory and Practice (IFIP AI), Milano
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Angiulli Fabrizio; Basta Stefano (literal)

Pagina inizio

• 309 (literal)

Pagina fine

• 318 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume

• ARTIFICIAL INTELLIGENCE IN THEORY AND PRACTICE II (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana

• 276 (literal)

Note

• ISI Web of Science (WOS) (literal)
• Google Scholar (literal)
• Scopu (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• DEIS-UNICAL; ICAR-CNR (literal)

Titolo

• Optimal Subset Selection for Classification through SAT Encodings (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn

• 978-0-387-09694-0 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume

• Bramer, M (literal)

Abstract

• In this work we propose a method for computing a minimum size training set consistent subset for the Nearest Neighbor rule (also said CNN problem) via SAT encodings. We introduce the SAT-CNN algorithm, which exploits a suitable encoding of the CNN problem in a sequence of SAT problems in order to exactly solve it, provided that enough computational resources are available. Comparison of SAT-CNN with well-known greedy methods shows that SAT-CNN is able to return a better solution. The proposed approach can be extended to several hard subset selection classification problems. (literal)

Prodotto di

• Institute for high performance computing and networking (ICAR) (Istituto)
• Gestire, Estrarre Conoscenza e Ragionare sui Dati (ICT.P08.002.001) (Modulo)

Autore CNR

• STEFANO BASTA (Unità di personale interno)

Incoming links:

Prodotto

• Institute for high performance computing and networking (ICAR) (Istituto)
• Gestire, Estrarre Conoscenza e Ragionare sui Dati (ICT.P08.002.001) (Modulo)

Autore CNR di

• STEFANO BASTA (Unità di personale interno)