Two variations on Fisher's linear discriminant for pattern recognition

被引：55

作者：

Cooke, T ^{[1
]}

机构：

[1] Ctr Sensor Signal & Informat Proc, Mawson Lakes, SA 5096, Australia

来源：

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 2002年 / 24卷 / 02期

关键词：

linear discriminant; classification;

D O I：

10.1109/34.982904

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Discriminants are often used in pattern recognition to separate clusters of points in some multidimensional "feature" space. This 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.

引用

页码：268 / 273

页数：6

共 10 条

[1] CLASSIFICATION INTO 2 MULTIVARIATE NORMAL-DISTRIBUTIONS WITH DIFFERENT COVARIANCE MATRICES [J].

ANDERSON, TW ;

BAHADUR, RR .

ANNALS OF MATHEMATICAL STATISTICS, 1962, 33 (02) :420-&

[2] A tutorial on Support Vector Machines for pattern recognition [J].

Burges, CJC .

DATA MINING AND KNOWLEDGE DISCOVERY, 1998, 2 (02) :121-167

[3]

Chapelle O, 2000, CHOOSING KERNEL PARA

[4]

COOKE T, IN PRESS J MULTIVARI

[5] The use of multiple measurements in taxonomic problems [J].

Fisher, RA .

ANNALS OF EUGENICS, 1936, 7 :179-188

[6]

Hart P.E., 1973, Pattern recognition and scene analysis

[7]

Joachims J., 1999, ADV KERNEL METHODS S

[8]

Mika S., 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468), P41, DOI 10.1109/NNSP.1999.788121

[9]

MIKA S, 2001, P AISTATS, P98

[10]

Vapnik V., 1998, STAT LEARNING THEORY, V1, P2

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