TY  - CHAP
AU  - Fernando Vilariño
AU  - Debora Gil
AU  - Petia Radeva
ED  - J. Vitrià, P. Radeva and I. Aguiló
PY  - 2004//
TI  - A Novel FLDA Formulation for Numerical Stability Analysis
BT  - Recent Advances in Artificial Intelligence Research and Development
SP  - 77
EP  - 84
VL  - 113
PB  - IOS Press
KW  - Supervised Learning
KW  - Linear Discriminant Analysis
KW  - Numerical Stability
KW  - Computer Vision
N2  - Fisher Linear Discriminant Analysis (FLDA) is one of the most popular techniques used in classification applying dimensional reduction. The numerical scheme involves the inversion of the within-class scatter matrix, which makes FLDA potentially ill-conditioned when it becomes singular. In this paper we present a novel explicit formulation of FLDA in terms of the eccentricity ratio and eigenvector orientations of the within-class scatter matrix. An analysis of this function will characterize those situations where FLDA response is not reliable because of numerical instability. This can solve common situations of poor classification performance in computer vision.
SN  - 978-1-58603-466-5
UR  - http://www.iospress.nl/loadtop/load.php?isbn=9781586034665
L1  - http://refbase.cvc.uab.es/files/VGR2004.pdf
N1  - MV;IAM;MILAB;SIAI
ID  - Fernando Vilariño2004
ER  -