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Regression level set estimation via cost-sensitive classification

Author
SCOTT, Clayton1 ; DAVENPORT, Mark2
[1] Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, United States
[2] Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States
Source

IEEE transactions on signal processing. 2007, Vol 55, Num 6, pp 2752-2757, 6 p ; 1 ; ref : 17 ref

CODEN
ITPRED
ISSN
1053-587X
Scientific domain
Telecommunications
Publisher
Institute of Electrical and Electronics Engineers, New York, NY
Publication country
United States
Document type
Article
Language
English
Author keyword
Cost-sensitive classification learning reduction regression level set estimation supervised learning
Keyword (fr)
Apprentissage supervisé Classification signal Diminution coût Estimation coût Histogramme Machine vecteur support Minimisation coût Plus proche voisin
Keyword (en)
Supervised learning Signal classification Cost lowering Cost estimation Histogram Support vector machine Cost minimization Nearest neighbour
Keyword (es)
Aprendizaje supervisado Reducción costes Estimación costo Histograma Máquina vector soporte Minimización costo Vecino más cercano
Classification
Pascal
001 Exact sciences and technology / 001D Applied sciences / 001D04 Telecommunications and information theory / 001D04A Information, signal and communications theory / 001D04A04 Signal and communications theory / 001D04A04A Signal, noise / 001D04A04A1 Signal representation. Spectral analysis

Discipline
Telecommunications and information theory
Origin
Inist-CNRS
Database
PASCAL
INIST identifier
18787119

Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS

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