Hee-Joong Kang

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The performance of multiple classifier systems varies with the performance of component classifiers as well as the method of combination. In this paper, information-theoretic methods are proposed for constructing multiple classifier systems, provided that the number of component classifiers is constrained in advance. These proposed methods are applied to a(More)
Without an independence assumption, combining multiple classifiers deals with a high order probability distribution composed of classifiers and a class label. Storing and estimating the high order probability distribution is exponentially complex and unmanageable in theoretical analysis , so we rely on an approximation scheme using the dependency. In this(More)