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On dimensionality, sample size, and classification error of nonparametric linear classification algorithms

โœ Scribed by Raudys, S.


Book ID
117873365
Publisher
IEEE
Year
1997
Tongue
English
Weight
70 KB
Volume
19
Category
Article
ISSN
0162-8828

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Theoretical accuracies are studied for asymtotic approximations of the expected probabilities of misclassification (EPMC) when the linear discriminant function is used to classify an observation as coming from one of two multivariate normal populations with a common covariance matrix. The asymptotic