Abstract
By means of a general theorem, the space of the variables of classification is separated into population regions such that the probability of a correct classification is maximized. The theorem holds for any number of populations and variables but requires a knowledge of poppulation parameters and probabilities. A second theorem yields a large sample criterion for determining an optimum set of estimates for the unknown parameters. The two theorems combine to yield a large sample solution to the problem of how best to discriminate between two or more populations.
Citation
P. G. Hoel. R. P. Peterson. "A Solution to the Problem of Optimum Classification." Ann. Math. Statist. 20 (3) 433 - 438, September, 1949. https://doi.org/10.1214/aoms/1177729995
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