Learning and Forgetting with Local Information of New Objects
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Otros documentos de la autoría: Sánchez Garreta, Josep Salvador; Vázquez, Fernando D.; Pla, Filiberto
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7038
comunitat-uji-handle3:10234/159830
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INVESTIGACIONMetadatos
Título
Learning and Forgetting with Local Information of New ObjectsFecha de publicación
2008Editor
Springer VerlagISBN
978-3-540-85920-8ISSN
03029743Cita bibliográfica
Vázquez F.D., Sánchez J.S., Pla F. (2008) Learning and Forgetting with Local Information of New Objects. In: Ruiz-Shulcloper J., Kropatsch W.G. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2008. Lecture Notes in Computer Science, vol 5197. Springer, Berlin, Heidelberg.Tipo de documento
info:eu-repo/semantics/conferenceObjectVersión
info:eu-repo/semantics/acceptedVersionPalabras clave / Materias
Resumen
The performance of supervised learners depends on the presence of a
relatively large labeled sample. This paper proposes an automatic ongoing
learning system, which is able to incorporate new knowledge from the
e ... [+]
The performance of supervised learners depends on the presence of a
relatively large labeled sample. This paper proposes an automatic ongoing
learning system, which is able to incorporate new knowledge from the
experience obtained when classifying new objects and correspondingly, to
improve the efficiency of the system. We employ a stochastic rule for
classifying and editing, along with a condensing algorithm based on local
density to forget superfluous data (and control the sample size). The
effectiveness of the algorithm is experimentally evaluated using a number of
data sets taken from the UCI Machine Learning Database Repository. [-]
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info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess