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Based on the theoretical results, the paper proposes two methods to construct a scoring function for binary classification problems based on sequential Monte Carlo and an expectation-propagation (EP) algorithms, respectively. The performance was evaluated using well-known benchmark data sets and more realistic DNA data set.