LINEAR DECISION FUNCTIONS FOR PATTERN CLASSIFICATION

Sik-Sang Yau; TT LIN TT

LINEAR DECISION FUNCTIONS FOR PATTERN CLASSIFICATION

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Linear decision functions approximating the optimal decision functions in the least-mean-square-error sense are determined. By choosing a particular form of optimal decision functions, it is possible to evaluate the linear decision functions explicitly. It is found that this approach embodies some existing methods for evaluating linear discriminant functions, and is applicable to more general performance criteria. An iterative algorithm which improves the performance of the linear classifier based on linear decision functions substantially is proposed.

Original language	English (US)
Title of host publication	Unknown Host Publication Title
Pages	448-452
Number of pages	5
State	Published - 1968
Externally published	Yes
Event	Princeton Univ-2nd Annual Princeton Conference on Information Sciences & Systems-Proc - Duration: Mar 25 1968 → Mar 26 1968

Other

Other	Princeton Univ-2nd Annual Princeton Conference on Information Sciences & Systems-Proc
Period	3/25/68 → 3/26/68

ASJC Scopus subject areas

General Engineering

Cite this

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title = "LINEAR DECISION FUNCTIONS FOR PATTERN CLASSIFICATION",

abstract = "Linear decision functions approximating the optimal decision functions in the least-mean-square-error sense are determined. By choosing a particular form of optimal decision functions, it is possible to evaluate the linear decision functions explicitly. It is found that this approach embodies some existing methods for evaluating linear discriminant functions, and is applicable to more general performance criteria. An iterative algorithm which improves the performance of the linear classifier based on linear decision functions substantially is proposed.",

author = "Sik-Sang Yau and {LIN TT}, TT",

year = "1968",

language = "English (US)",

pages = "448--452",

booktitle = "Unknown Host Publication Title",

note = "Princeton Univ-2nd Annual Princeton Conference on Information Sciences & Systems-Proc ; Conference date: 25-03-1968 Through 26-03-1968",

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TY - CHAP

T1 - LINEAR DECISION FUNCTIONS FOR PATTERN CLASSIFICATION

AU - Yau, Sik-Sang

AU - LIN TT, TT

PY - 1968

Y1 - 1968

N2 - Linear decision functions approximating the optimal decision functions in the least-mean-square-error sense are determined. By choosing a particular form of optimal decision functions, it is possible to evaluate the linear decision functions explicitly. It is found that this approach embodies some existing methods for evaluating linear discriminant functions, and is applicable to more general performance criteria. An iterative algorithm which improves the performance of the linear classifier based on linear decision functions substantially is proposed.

AB - Linear decision functions approximating the optimal decision functions in the least-mean-square-error sense are determined. By choosing a particular form of optimal decision functions, it is possible to evaluate the linear decision functions explicitly. It is found that this approach embodies some existing methods for evaluating linear discriminant functions, and is applicable to more general performance criteria. An iterative algorithm which improves the performance of the linear classifier based on linear decision functions substantially is proposed.

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UR - http://www.scopus.com/inward/citedby.url?scp=0014372203&partnerID=8YFLogxK

M3 - Chapter

AN - SCOPUS:0014372203

SP - 448

EP - 452

BT - Unknown Host Publication Title

T2 - Princeton Univ-2nd Annual Princeton Conference on Information Sciences & Systems-Proc

Y2 - 25 March 1968 through 26 March 1968

ER -

LINEAR DECISION FUNCTIONS FOR PATTERN CLASSIFICATION

Abstract

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ASJC Scopus subject areas

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