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In order to use combinative classifiers to effectively solve large-scale learning problems, this paper focuses on the following aspects. (A) Decomposition of large-scale learning problems. (B) Selection of units of combinative classifiers. (C) Transformation of outputs of single classifiers into the grades of membership. We select improved kernel Fisher, Mahalanobis distance, and 10-nearest-neighbor...