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A theoretical comparison of two-class Fisher's and heteroscedastic linear dimensionality reduction schemes

Author
RUEDA, Luis1 ; HERRERA, Myriam2
[1] Member of the IEEE, School of Computer Science, University of Windsor, 401 Sunset Avenue, Windsor, ON, N9B 3P4, Canada
[2] Department and Institute of Informatics, National University of San Juan. Cereceto y Meglioli, San Juan 5400, Argentina
Source

Pattern recognition letters. 2008, Vol 29, Num 16, pp 2092-2098, 7 p ; ref : 1/4 p

CODEN
PRLEDG
ISSN
0167-8655
Scientific domain
Computer science; Telecommunications
Publisher
Elsevier, Amsterdam
Publication country
Netherlands
Document type
Article
Language
English
Author keyword
Classification error Heteroscedastic classifiers Linear dimensionality reduction
Keyword (fr)
Classification automatique Classification signal Condition nécessaire suffisante Covariance Diagonalisation Méthode statistique Probabilité a priori Transformation distance Transformation linéaire
Keyword (en)
Automatic classification Signal classification Necessary and sufficient condition Covariance Diagonalization Statistical method Prior probability Distance transformation Linear transformation
Keyword (es)
Clasificación automática Condición necesaria suficiente Covariancia Diagonalización Método estadístico Probabilidad a priori Transformación distancia Transformación lineal
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
20828958

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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