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# System Evaluation of Construction Methods for Multi-class Problems using Binary Classirers

Construction methods for multi-valued classification (multi-class) systems using binary classifiers are discussed and evaluated by a trade-off model for system evaluation based on rate-distortion theory. Suppose the multi-class systems consisted of M(/geq 3) categories and N(/geq {M -1}) binary classifiers, then they can be represented by a matrix W, where the matrix W is given by a table of M code words with length N, called a code word table. Applying document classification data, the relationships between the probability of classification error Pe and the number of binary classifiers N for given M are investigated, and we show that the systems have desirable properties such as \Flexible", \Elastic", and so on. Additionally, hand-written alphabet recognition data are examined, and we show that the desirable properties are also supported.