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The generalization capability is usually recognized as the most desired feature of data-driven learning systems, such as classifiers. However, in many practical applications obtaining human-understandable information, relevant to the problem at hand, from the classidication model can be equally important. In this paper we propose a classification system able to fulfill these two requirements simultaneously...
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