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A Generalized Discriminant Rule When Training Population and Test Population Differ on Their Descriptive Parameters
2002
Biometrics
Standard discriminant analysis methods make the assumption that both the labeled sample used to estimate the discriminant rule and the non-labeled sample on which this rule is applied arise from the same population. In this work, we consider the case where the two populations are slightly different. In the multinormal context, we establish that both populations are linked through linear mapping. Estimation of the non-labeled sample discriminant rule is then obtained by estimating parameters of
doi:10.1111/j.0006-341x.2002.00387.x
pmid:12071412
fatcat:56al6rmklrawblidzbet2illd4