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We have developed a novel clustering and quantization algorithm that allows the user to create multiple one-topone correspondences between the actual data and its transformed (clustered and quantized) values, based on the user's hypothesis regarding the nature of the classification task. The types of problems for which the algorithm can be beneficial are discussed. We report experiments employing...
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