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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