This chapter sums up and proposes some results related to classification problem by Bayesian method. We present the classification principle, Bayes error, and establish its relationship with other measures. The determination for Bayes error in reality for one and multi-dimensions is also considered. Based on training set and the object that we need to classify, an algorithm to determine the prior probability that can make to reduce Bayes error is proposed. This algorithm has been performed by the MATLAB procedure that can be applied well with real data. The proposed algorithm is applied in three domains: biology, medicine, and economics through specific problems. With different characteristics of applied data sets, the proposed algorithm always gives the best results in comparison to the existing ones. Furthermore, the examples show the feasibility and potential application in reality of the researched problem.
Part of the book: Bayesian Inference