Implementing reliable learning through Reliable Support Vector Machines (Contributo in atti di convegno)

Type

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

Label

• Implementing reliable learning through Reliable Support Vector Machines (Contributo in atti di convegno) (literal)

Anno

• 2011-01-01T00:00:00+01:00 (literal)

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

• 10.1109/FOCI.2011.5949475 (literal)

Alternative label

• E. Ferrari, M. Muselli (2011)
  Implementing reliable learning through Reliable Support Vector Machines
  in 2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI), Paris, France, 11-15 April 2011
  (literal)

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

• E. Ferrari, M. Muselli (literal)

Pagina inizio

• 100 (literal)

Pagina fine

• 106 (literal)

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

• Proceedings of the 2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI) (literal)

Note

• Scopu (literal)

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

• E. Ferrari, M. Muselli: CNR-IEIIT, Genova, Italy (literal)

Titolo

• Implementing reliable learning through Reliable Support Vector Machines (literal)

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

• 978-1-4244-9981-6 (literal)

Abstract

• Starting from the theoretical framework of reliable learning, a new classification algorithm capable of using prior information on the reliability of a training set has been developed. It consists in a straightforward modification of the standard technique adopted in the conventional Support Vector Machine (SVM) approach: the knowledge about reliability, encoded by adding a binary label to each example of the training set (asserting if the classification is reliable or not), is employed to properly modify the constrained optimization problem for the generalized optimal hyperplane. Hence, the name Reliable Support Vector Machines (RSVM) is adopted for models built according to the proposed algorithm. Specific tests have been carried out to verify how RSVM performs in comparison with standard SVM, showing a significant improvement in classification accuracy. (literal)

Prodotto di

• Machine Learning for Biological Data (INT.P02.002.001) (Modulo)
• Istituto di elettronica e di ingegneria dell'informazione e delle telecomunicazioni (IEIIT) (Istituto)

Autore CNR

• MARCO MUSELLI (Unità di personale interno)
• ENRICO FERRARI (Persona)

Incoming links:

Prodotto

• Istituto di elettronica e di ingegneria dell'informazione e delle telecomunicazioni (IEIIT) (Istituto)
• Machine Learning for Biological Data (INT.P02.002.001) (Modulo)

Autore CNR di

• MARCO MUSELLI (Unità di personale interno)
• ENRICO FERRARI (Persona)