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A solution for the traditional Bayesian classification problem in non-traditional conditions is proposed, when the distributions and a priori probabilities of classes are unknown, but a trained sample from the zero class (labeled positive) and mixed sample (unlabeled) are available. Mixed sample will be employed in the learning to restore mixed distribution and as a test sample for constructed classifier...
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