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Multiclass Bayes error estimation by a feature space sampling technique (1979)

Mobasseri, B. G. ; Mcgillem, C. D.

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Publication Date: 2019-06-27

Description: A general Gaussian M-class N-feature classification problem is defined. An algorithm is developed that requires the class statistics as its only input and computes the minimum probability of error through use of a combined analytical and numerical integration over a sequence simplifying transformations of the feature space. The results are compared with those obtained by conventional techniques applied to a 2-class 4-feature discrimination problem with results previously reported and 4-class 4-feature multispectral scanner Landsat data classified by training and testing of the available data.

Keywords: STATISTICS AND PROBABILITY

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