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This paper tackles the problem of decremental learning of an evolving classification system. We study the use of decremental learning to improve performance of evolving recognizers in non-stationary scenarios. Our on-line recognizer is based on an evolving fuzzy inference system. In this paper, we propose a new strategy to introduce decremental learning, with the use of a sliding window, in the optimization of fuzzy rules conclusions. This approach is based on a downdating technique of leastdoi:10.1109/icmla.2012.110 dblp:conf/icmla/BouillonAA12 fatcat:m3phodua4bgcthoi5ktfrq44wu