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Estimating the Expected Probability of Misclassification for a Rule Based on the Linear Discriminant Function: Univariate Normal Case

 

作者: M. Sorum,  

 

期刊: Technometrics  (Taylor Available online 1973)
卷期: Volume 15, issue 2  

页码: 329-339

 

ISSN:0040-1706

 

年代: 1973

 

DOI:10.1080/00401706.1973.10489046

 

出版商: Taylor & Francis Group

 

关键词: Classification;Linear Discriminant Function;Probabilities of Misclassification

 

数据来源: Taylor

 

摘要:

The problem is to estimate the average probability of misclassifying an observation from a given population in the context of the two group classification problem when populations are univariate normal with unknown means and common known variance, and the rule is based on the linear discriminant function. Several estimators are compared with respect to asymptotic MSE and with respect to the distribution of the absolute error between estimator and parameter, and conclusions drawn about the best estimators.

 

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