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In this paper we give a survey of the combination of classifiers. We briefly describe basic principles of machine learning and the problem of classifier construction and review several approaches to generate different classifiers as well as established methods to combine different classifiers. Then, we introduce our novel approach to assess the appropriateness of different classifiers based on their characteristics for each test point individuallydoi:10.5130/ajict.v5i2.1152 fatcat:te62fthrlbhrdm3e3ddg3pmgga