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In data stream, concept drift often occurs in an unpredictable way, the classifier model which was learned from previous data is not accurate to the current data, so regular updating of the model is necessary. Moreover, updating too frequently will cause a negative impact on the clustering accuracy and the analysis of subsequent data. This paper proposed a model-updating mechanism for data streams...
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