Estimating the probability of misclassification and variate selection |
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Authors: | TL Boullion PL Odell BS Duran |
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Affiliation: | Department of Mathematics, Texas Tech University, P.O. Box 4319, Lubbock, Texas 79409, U.S.A. |
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Abstract: | This paper considers the problem of estimating the probability of misclassifying normal variates using the usual discriminant function when the parameters are unknown. The probability of misclassification is estimated, by Monte Carlo simulation, as a function of n1 and n2 (sample sizes), p (number of variates) and α (measure of separation between the two populations). The probability of misclassification is used to determine, for a given situation, the best number and subset of variates for various sample sizes. An example using real data is given. |
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Keywords: | Discrimination Multivariate normal Probability of misclassification Simulation Divergence Mahalanobis distance Remote sensing data |
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