DocumentCode
1560331
Title
Two variations on Fisher´s linear discriminant for pattern recognition
Author
Cooke, Tristrom
Author_Institution
Center for Sensor Signal & Inf. Process., Mawson Lakes, SA, Australia
Volume
24
Issue
2
fYear
2002
fDate
2/1/2002 12:00:00 AM
Firstpage
268
Lastpage
273
Abstract
Discriminants are often used in pattern recognition to separate clusters of points in some multidimensional "feature" space. The paper provides two fast and simple techniques for improving on the classification performance provided by Fisher\´s linear discriminant for two classes. Both of these methods are also extended to nonlinear decision surfaces through the use of Mercer kernels
Keywords
decision theory; learning automata; pattern classification; probability; search problems; Fisher linear discriminant; Mercer kernels; classification performance; clusters; learning automata; multidimensional feature space; nonlinear decision surfaces; pattern recognition; support vector machines; Fractals; Histograms; Kernel; Linear discriminant analysis; Multidimensional systems; Pattern recognition; Radar detection; Robustness; Testing; Vehicle detection;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.982904
Filename
982904
Link To Document