Prototype-based classification in unbalanced biomedical problems (Contributo in volume (capitolo o saggio))

Type

• Contributo in volume (capitolo o saggio) (Classe)
• Prodotto della ricerca (Classe)

Label

• Prototype-based classification in unbalanced biomedical problems (Contributo in volume (capitolo o saggio)) (literal)

Anno

• 2010-01-01T00:00:00+01:00 (literal)

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

• 10.1007/978-3-642-14078-5_7 (literal)

Alternative label

• Colantonio S.; Little S.; Salvetti O.; Perner P. (2010)
  Prototype-based classification in unbalanced biomedical problems
  in Successful Case-based Reasoning Applications, 2010
  (literal)

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

• Colantonio S.; Little S.; Salvetti O.; Perner P. (literal)

Pagina inizio

• 143 (literal)

Pagina fine

• 163 (literal)

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

• Heidelberg/New York (literal)

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

• http://www.springerlink.com/content/c18qp407273n5x84/ (literal)

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

• Successful Case-based Reasoning Applications (literal)

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

• 305 (literal)

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

• In: Successful Case-based Reasoning Applications. Montani Stefania, Jain Lakhmi C. ed. pp. 143 - 163. (Studies in Computational Intelligence, vol. 305). Heidelberg/New York: Springer, 2010. (literal)

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

• 21 (literal)

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

• Medical diagnosis can be easily assimilated to a classification problem devoted at identifying the presence or not of a disease. Since a pathology is often much rarer than the healthy condition, medical diagnosis may require a classifier to cope with the problem of under-represented classes. Class imbalance, which has revealed rather common in many other application domains, contravenes the traditional assumption of machine learning methods about the similar prior probabilities of target classes. In this respect, due to their unrestricted generalization ability, classifiers such as decision trees and Naïve Bayesian are not the proper classification methods. On the contrary, the basic feature of case-based classifiers to reason on representative samples of each class makes them appear a more suitable method for such a task. In this chapter, the behavior of a case-based classifier, ProtoClass, on unbalanced biomedical classification problems is evaluated in different settings of the case (literal)

Note

• Google Scholar (literal)
• Scopu (literal)

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

• CNR-ISTI, Pisa, Italy; Institute of Computer Vision and Applied Computer Sciences (IBaI), Leipzig - Germany (literal)

Titolo

• Prototype-based classification in unbalanced biomedical problems (literal)

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

• Successful Case-based Reasoning Applications (literal)

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

• 978-3-642-14077-8 (literal)

Abstract

• Medical diagnosis can be easily assimilated to a classification problem devoted at identifying the presence or not of a disease. Since a pathology is often much rarer than the healthy condition, medical diagnosis may require a classifier to cope with the problem of under-represented classes. Class imbalance, which has revealed rather common in many other application domains, contravenes the traditional assumption of machine learning methods about the similar prior probabilities of target classes. In this respect, due to their unrestricted generalization ability, classifiers such as decision trees and Naïve Bayesian are not the proper classification methods. On the contrary, the basic feature of case-based classifiers to reason on representative samples of each class makes them appear a more suitable method for such a task. In this chapter, the behavior of a case-based classifier, ProtoClass, on unbalanced biomedical classification problems is evaluated in different settings of the case-base configuration. Comparison with other classification methods showed the effectiveness of such an approach to unbalanced classification problems and, hence, to medical diagnostic classification. (literal)

Prodotto di

• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)
• Elaborazione di segnali e immagini per impieghi diagnostici e interpretazione di immagini multisorgente (ICT.P10.012.001) (Modulo)

Autore CNR

• OVIDIO SALVETTI (Persona)
• SARA COLANTONIO (Persona)

Insieme di parole chiave

• Keywords of "Prototype-based classification in unbalanced biomedical problems" (Insieme di parole chiave)

Incoming links:

Autore CNR di

• OVIDIO SALVETTI (Persona)
• SARA COLANTONIO (Persona)

Prodotto

• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)
• Elaborazione di segnali e immagini per impieghi diagnostici e interpretazione di immagini multisorgente (ICT.P10.012.001) (Modulo)

Insieme di parole chiave di

• Keywords of "Prototype-based classification in unbalanced biomedical problems" (Insieme di parole chiave)