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In this paper the recently introduced evolving fuzzy classifier method called eClass is studied in respect to its architecture and evolution of the fuzzy rule-base. The proposed classifier has an open/evolving structure and can start 'from scratch', learning and adapting to the new data samples. Alternatively, if an initial fuzzy rule-based classifier, generated beforehand in off-line mode or provided...
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