Estimating the Bayes Risk from Sample Data
نویسندگان
چکیده
A new nearest-neighbor method is described for estimating the Bayes risk of a multiclass pattern claSSification problem from sample data (e.g., a classified training set). Although it is assumed that the classification problem can be accurately described by sufficiently smooth class-conditional distributions, neither these distributions, nor the corresponding prior probabilities of the classes are required. Thus this method can be applied to practical problems where the underlying probabilities are not known. This method is illustrated using two different pattern recognition problems.
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