AWSum-Combining Classification with Knowledge Aquisition

Détails

Ressource 1Télécharger: BIB_81E1452DC381.P001.pdf (1159.15 [Ko])
Etat: Serval
Version: Final published version
ID Serval
serval:BIB_81E1452DC381
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
AWSum-Combining Classification with Knowledge Aquisition
Périodique
International Journal of Software and Informatics
Auteur(s)
Quinn A., Stranieri A., Yearwood J., Hafen G., Jeline H.
ISSN
1673-7288
Statut éditorial
Publié
Date de publication
2008
Peer-reviewed
Oui
Volume
2
Numéro
2
Pages
199-214
Langue
anglais
Résumé
Many classifiers achieve high levels of accuracy but have limited applicability in real world situations because they do not lead to a greater understanding or insight into the^way features influence the classification. In areas such as health informatics a classifier that clearly identifies the influences on classification can be used to direct research and formulate interventions. This research investigates the practical applications of Automated Weighted
Sum, (AWSum), a classifier that provides accuracy comparable to other techniques whilst providing insight into the data. This is achieved by calculating a weight for each feature value that represents its influence on the class value. The merits of this approach in classification and insight are evaluated on a Cystic Fibrosis and Diabetes datasets with positive results.
Mots-clé
data mining, classification, knowledge acquisition, weighted sum
Création de la notice
26/01/2009 16:59
Dernière modification de la notice
03/03/2018 18:48
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