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- W2105187789 abstract "In many pattern classification problems, an estimate of the posterior probabilities (rather than only a classification) is required. This is usually the case when some confidence measure in the classification is needed. In this article, we propose a new posterior probability estimator. The proposed estimator considers the K-nearest neighbors. It attaches a weight to each neighbor that contributes in an additive fashion to the posterior probability estimate. The weights corresponding to the K-nearest-neighbors (which add to 1) are estimated from the data using a maximum likelihood approach. Simulation studies confirm the effectiveness of the proposed estimator." @default.
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- W2105187789 date "2005-03-01" @default.
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- W2105187789 title "Estimating the Posterior Probabilities Using the <i>K</i>-Nearest Neighbor Rule" @default.
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- W2105187789 doi "https://doi.org/10.1162/0899766053019971" @default.
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