Linear discrimination for three known normal populations |
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Authors: | Mark J Schervish |
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Institution: | Department of Statistics, Carnegie-Mellon University, Pittsburgh, PA 15213, USA |
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Abstract: | A random vector is assumed to have one of three known multivariate normal distributions with equal covariance matrices. It is desired to separate the three distributions by means of a single linear discriminant function. Such a function can lead to a classification rule. The function whose classification rule minimizes the average of the three probabilities of misclassification is found. Also the function is found whose rule minimizes the maximum of the three probabilities of misclassification. |
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Keywords: | Primary 62H30 Secondary 62C25 Classification Bayes rule Minimax rule |
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